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CIT: CAUSAL INFERENCE TEST VERSION 2.3.1 FROM CRANAUTHOR: JOSHUA
MILLSTEIN
The hypothesis test generates a p-value or permutation-based FDR value with confidence intervals to quantify uncertainty in the causal inference. The outcome can be represented by either a continuous or binary variable, the potential mediator is continuous, and the instrumental variable can be continuous or binary and is not limitedto a single
HTMLTOOLS: TOOLS FOR HTML VERSION 0.5.1.1 FROM CRAN Tools for HTML generation and output. as.tags: Convert a value to tags browsable: Make an HTML object browsable builder: HTML Builder Functions capturePlot: Capture a plot as a saved file copyDependencyToDir: Copy an HTML dependency to a directory css: CSS string helper defaultPngDevice: Determine the best PNG device for your system findDependencies: Collect attached SNFTOOL: SIMILARITY NETWORK FUSION VERSION 2.3.0 FROM CRAN SNFtool: Similarity Network Fusion. Similarity Network Fusion takes multiple views of a network and fuses them together to construct an overall status matrix. The input to our algorithm can be feature vectors, pairwise distances, or pairwise similarities. The learned status matrix can then be used for retrieval, clustering, andclassification.
VARIABLEFEATURES: HIGHLY VARIABLE FEATURES IN SEURATOBJECT In SeuratObject: Data Structures for Single Cell Data. Description Usage Arguments Value Examples. View source: R/generics.R. Description. Get and set variable feature information for an Assay object.HVFInfo and VariableFeatures utilize generally variable features, while SVFInfo and SpatiallyVariableFeatures are restricted to spatially variable features . Usage EXTREMEVALUES: AN R PACKAGE FOR OUTLIER DETECTION IN This package offers outlier detection and plot functions for univariate data. The package is the implementation of the outlier detection methods introduced in the reference below. Briefly, the methods work as follows. Using a subset of the data, the parameters for a model distribution are estimated using regression of the sorted data on their QQ-plot positions. A value in the data is an XJSUN1221/TINYARRAY: SIMPLIFY GEO AND TCGA ANALYSIS AND Simplify geo and tcga analysis and plots. box_surv: box_surv cor.full: cor.test for all varibles cor.one: cor.test for one varible with all varibles double_enrich: draw enrichment bar plots for both up and down genes draw_boxplot: draw boxplot for expression draw_heatmap: draw a heatmap plot draw_heatmap2: draw heatmap plots draw_pca: draw PCA plots draw_venn: draw a venn plot SEMPLOT: PATH DIAGRAMS AND VISUAL ANALYSIS OF VARIOUS SEM cvregsemplot: Bridge between cv_regsem output and sempaths edits: Functions to facilitate editting 'semPlotModel' objects. Imin: Helper function to substract matrix from identity matrix and lisrelModel: Construct SEM model using LISREL matrix specification. modelMatrices: Extract SEM model matrices ramModel: Construct SEM model using RAM matrix specification. NLSWORK: NATIONAL LONGITUDINAL SURVEY OF YOUNG WORKINGSEE MORE ONRDRR.IO
GUYOT.METHOD: GO FROM KM CURVE DATA FROM PUBLISHED FIGURES This function is a simple adaptation of code given by Guyot et al. add_baseline_column: add_baseline_column check_connected: check_connected guyot.method: Go from KM curve data from published figures into hazard_plot: hazard_plot hazard_table: hazard_table mrcc_small: A dataset containing survival times of individuals undergoing prep_all_hazards: prep_all_hazards GPA2: GPA2 IN WOOLDRIDGE: 111 DATA SETS FROM "INTRODUCTORY Format. A data.frame with 4137 observations on 12 variables: sat: combined SAT score tothrs: total hours through fall semest colgpa: GPA after fall semester athlete: =1 if athlete verbmath: verbal/math SAT score hsize: size grad. class, 100s hsrank: rank in grad. class hsperc: high school percentile, from top female: =1 if female white: =1 if white black: =1 if black XJSUN1221/TINYARRAY: SIMPLIFY GEO AND TCGA ANALYSIS ANDAUTHOR: XIAOJIESUN
Simplify geo and tcga analysis and plots. box_surv: box_surv cor.full: cor.test for all varibles cor.one: cor.test for one varible with all varibles double_enrich: draw enrichment bar plots for both up and down genes draw_boxplot: draw boxplot for expression draw_heatmap: draw a heatmap plot draw_heatmap2: draw heatmap plots draw_pca: draw PCA plots draw_venn: draw a venn plot LM.RIDGE: RIDGE REGRESSION IN MASS: SUPPORT FUNCTIONS AND an optional data frame, list or environment in which to interpret the variables occurring in formula . subset. expression saying which subset of the rows of the data should be used in the fit. All observations are included by default. na.action. a function to filter missing data. lambda. A scalar or vector of ridge constants. model. HTMLTOOLS: TOOLS FOR HTML VERSION 0.5.1.1 FROM CRAN Tools for HTML generation and output. as.tags: Convert a value to tags browsable: Make an HTML object browsable builder: HTML Builder Functions capturePlot: Capture a plot as a saved file copyDependencyToDir: Copy an HTML dependency to a directory css: CSS string helper defaultPngDevice: Determine the best PNG device for your system findDependencies: Collect attached SNFTOOL: SIMILARITY NETWORK FUSION VERSION 2.3.0 FROM CRAN SNFtool: Similarity Network Fusion. Similarity Network Fusion takes multiple views of a network and fuses them together to construct an overall status matrix. The input to our algorithm can be feature vectors, pairwise distances, or pairwise similarities. The learned status matrix can then be used for retrieval, clustering, andclassification.
SEMPLOT: PATH DIAGRAMS AND VISUAL ANALYSIS OF VARIOUS SEM cvregsemplot: Bridge between cv_regsem output and sempaths edits: Functions to facilitate editting 'semPlotModel' objects. Imin: Helper function to substract matrix from identity matrix and lisrelModel: Construct SEM model using LISREL matrix specification. modelMatrices: Extract SEM model matrices ramModel: Construct SEM model using RAM matrix specification. GENLASSO: PATH ALGORITHM FOR GENERALIZED LASSO PROBLEMS genlasso: Path Algorithm for Generalized Lasso Problems. Computes the solution path for generalized lasso problems. Important use cases are the fused lasso over an arbitrary graph, and trend fitting of any given polynomial order. Specialized implementations for the latter two subproblems are given to improve stability and speed. NLSWORK: NATIONAL LONGITUDINAL SURVEY OF YOUNG WORKINGSEE MORE ONRDRR.IO
REGISTER_GOOGLE: REGISTER A GOOGLE API IN GGMAP: SPATIAL bb2bbox: Convert a bb specification to a bbox specification calc_zoom: Calculate a zoom given a bounding box crime: Crime data file_drawer: Manage the ggmap file drawer. geocode: Geocode geom_leg: Single line segments with rounded ends get_cloudmademap: Get a CloudMade map. get_googlemap: Get a Google Map. get_map: Grab a map. get_navermap:Get a Naver Map
MRCIEU/IEUGWASR DOCUMENTATION The MRCIEU/ieugwasr package contains the following man pages: afl2_chrpos afl2_list afl2_rsid api_query api_status associations batches batch_from_id check_access_token cor dot-data editcheck fill_n get_access_token get_query_content gwasinfo infer_ancestry ld_clump ld_clump_api ld_clump_local ld_matrix ld_matrix_local ld_reflookup legacy_ids logging_info phewas pipe revoke_access_token GPA2: GPA2 IN WOOLDRIDGE: 111 DATA SETS FROM "INTRODUCTORY Format. A data.frame with 4137 observations on 12 variables: sat: combined SAT score tothrs: total hours through fall semest colgpa: GPA after fall semester athlete: =1 if athlete verbmath: verbal/math SAT score hsize: size grad. class, 100s hsrank: rank in grad. class hsperc: high school percentile, from top female: =1 if female white: =1 if white black: =1 if black META: GENERAL PACKAGE FOR META-ANALYSIS VERSION 4.18-1 amlodipine: Amlodipine for Work Capacity as.data.frame.meta: Additional functions for objects of class meta baujat.meta: Baujat plot to explore heterogeneity in meta-analysis bubble.metareg: Bubble plot to display the result of a meta-regression ci: Calculation of confidence intervals (based on normal cisapride: Cisapride inNon-Ulcer Dispepsia
POWDR: FULL PATTERN SUMMATION OF X-RAY POWDER DIFFRACTION afps: Automated full pattern summation afps.powdRlib: Automated full pattern summation bkg: Fit a background to XRPD data fps: Full pattern summation fps.powdRlib: Full pattern summation minerals: An example powdRlib reference library minerals_phases: A table of associated data for the minerals_xrd table, which minerals_regroup_structure: Example regrouping structure for the DINCERTI/CEA SOURCE: TESTS/TESTTHAT/TEST-PARAMS_MLOGIT_LIST.R absorbing: Absorbing states apply_rr: Apply relative risks to transition probability matrices as_array3: Convert between 2D tabular objects and 3D arrays as.data.table.tparams_transprobs: Coerce to 'data.table' as_pfs_os: Convert multi-state data to PFS and OS data autoplot.stateprobs: Plot state probabilities autoplot.survival: Plotsurvival curves
ROWR: ROW-BASED FUNCTIONS FOR R OBJECTS VERSION 1.1.3 FROM rowr: Row-Based Functions for R Objects. Provides utilities which interact with all R objects as if they were arranged in rows. It allows more consistent and predictable output to common functions, and generalizes a number of utility functions to to be failsafe with any number and type of input objects. SEMPLOT: PATH DIAGRAMS AND VISUAL ANALYSIS OF VARIOUS SEM cvregsemplot: Bridge between cv_regsem output and sempaths edits: Functions to facilitate editting 'semPlotModel' objects. Imin: Helper function to substract matrix from identity matrix and lisrelModel: Construct SEM model using LISREL matrix specification. modelMatrices: Extract SEM model matrices ramModel: Construct SEM model using RAM matrix specification. LOGFC: CALCULATE LOG-FOLD CHANGES FROM HURDLE MODEL Details. The log-fold change is defined as follows. For each gene, let u(x) be the expected value of the continuous component, given a covariate x and the estimated coefficients coefC, ie, u(x)= crossprod(x, coefC).Likewise, Let v(x)= 1/(1+exp(-crossprod(coefD, x))) be the expected value of the discrete component. The log fold change from contrast0 to contrast1 is defined as DECONTX: CONTAMINATION ESTIMATION WITH DECONTX IN CELDA x: A numeric matrix of counts or a SingleCellExperiment with the matrix located in the assay slot under assayName.Cells in each batch will be subsetted and converted to a sparse matrix of class dgCMatrix from package Matrix before analysis. This object should onlyRDRR.IO
rdrr.io
GENLASSO: PATH ALGORITHM FOR GENERALIZED LASSO PROBLEMS genlasso: Path Algorithm for Generalized Lasso Problems. Computes the solution path for generalized lasso problems. Important use cases are the fused lasso over an arbitrary graph, and trend fitting of any given polynomial order. Specialized implementations for the latter two subproblems are given to improve stability and speed. ZONGYF02/INORMUS: README.MD are_boxes_invalid: Helper to determine if coding boxes are valid check_admfrom_ihunits: The time from injury to hospital admission should be within check_condate_hspdate: Check that consent date should be 0 - 30 days after hospital check_condate_injdate: Check that consent date should be on the same day, or after check_form2.1_box5: Filters out invalid rows for box 5 of form2.1 CIT: CAUSAL INFERENCE TEST VERSION 2.3.1 FROM CRANAUTHOR: JOSHUAMILLSTEIN
The hypothesis test generates a p-value or permutation-based FDR value with confidence intervals to quantify uncertainty in the causal inference. The outcome can be represented by either a continuous or binary variable, the potential mediator is continuous, and the instrumental variable can be continuous or binary and is not limitedto a single
HTMLTOOLS: TOOLS FOR HTML VERSION 0.5.1.1 FROM CRAN Tools for HTML generation and output. as.tags: Convert a value to tags browsable: Make an HTML object browsable builder: HTML Builder Functions capturePlot: Capture a plot as a saved file copyDependencyToDir: Copy an HTML dependency to a directory css: CSS string helper defaultPngDevice: Determine the best PNG device for your system findDependencies: Collect attached SNFTOOL: SIMILARITY NETWORK FUSION VERSION 2.3.0 FROM CRAN SNFtool: Similarity Network Fusion. Similarity Network Fusion takes multiple views of a network and fuses them together to construct an overall status matrix. The input to our algorithm can be feature vectors, pairwise distances, or pairwise similarities. The learned status matrix can then be used for retrieval, clustering, andclassification.
VARIABLEFEATURES: HIGHLY VARIABLE FEATURES IN SEURATOBJECT In SeuratObject: Data Structures for Single Cell Data. Description Usage Arguments Value Examples. View source: R/generics.R. Description. Get and set variable feature information for an Assay object.HVFInfo and VariableFeatures utilize generally variable features, while SVFInfo and SpatiallyVariableFeatures are restricted to spatially variable features . Usage EXTREMEVALUES: AN R PACKAGE FOR OUTLIER DETECTION IN This package offers outlier detection and plot functions for univariate data. The package is the implementation of the outlier detection methods introduced in the reference below. Briefly, the methods work as follows. Using a subset of the data, the parameters for a model distribution are estimated using regression of the sorted data on their QQ-plot positions. A value in the data is an XJSUN1221/TINYARRAY: SIMPLIFY GEO AND TCGA ANALYSIS AND Simplify geo and tcga analysis and plots. box_surv: box_surv cor.full: cor.test for all varibles cor.one: cor.test for one varible with all varibles double_enrich: draw enrichment bar plots for both up and down genes draw_boxplot: draw boxplot for expression draw_heatmap: draw a heatmap plot draw_heatmap2: draw heatmap plots draw_pca: draw PCA plots draw_venn: draw a venn plot SEMPLOT: PATH DIAGRAMS AND VISUAL ANALYSIS OF VARIOUS SEM cvregsemplot: Bridge between cv_regsem output and sempaths edits: Functions to facilitate editting 'semPlotModel' objects. Imin: Helper function to substract matrix from identity matrix and lisrelModel: Construct SEM model using LISREL matrix specification. modelMatrices: Extract SEM model matrices ramModel: Construct SEM model using RAM matrix specification. NLSWORK: NATIONAL LONGITUDINAL SURVEY OF YOUNG WORKINGSEE MORE ONRDRR.IO
GUYOT.METHOD: GO FROM KM CURVE DATA FROM PUBLISHED FIGURES This function is a simple adaptation of code given by Guyot et al. add_baseline_column: add_baseline_column check_connected: check_connected guyot.method: Go from KM curve data from published figures into hazard_plot: hazard_plot hazard_table: hazard_table mrcc_small: A dataset containing survival times of individuals undergoing prep_all_hazards: prep_all_hazards GPA2: GPA2 IN WOOLDRIDGE: 111 DATA SETS FROM "INTRODUCTORY Format. A data.frame with 4137 observations on 12 variables: sat: combined SAT score tothrs: total hours through fall semest colgpa: GPA after fall semester athlete: =1 if athlete verbmath: verbal/math SAT score hsize: size grad. class, 100s hsrank: rank in grad. class hsperc: high school percentile, from top female: =1 if female white: =1 if white black: =1 if black CIT: CAUSAL INFERENCE TEST VERSION 2.3.1 FROM CRANAUTHOR: JOSHUAMILLSTEIN
The hypothesis test generates a p-value or permutation-based FDR value with confidence intervals to quantify uncertainty in the causal inference. The outcome can be represented by either a continuous or binary variable, the potential mediator is continuous, and the instrumental variable can be continuous or binary and is not limitedto a single
HTMLTOOLS: TOOLS FOR HTML VERSION 0.5.1.1 FROM CRAN Tools for HTML generation and output. as.tags: Convert a value to tags browsable: Make an HTML object browsable builder: HTML Builder Functions capturePlot: Capture a plot as a saved file copyDependencyToDir: Copy an HTML dependency to a directory css: CSS string helper defaultPngDevice: Determine the best PNG device for your system findDependencies: Collect attached SNFTOOL: SIMILARITY NETWORK FUSION VERSION 2.3.0 FROM CRAN SNFtool: Similarity Network Fusion. Similarity Network Fusion takes multiple views of a network and fuses them together to construct an overall status matrix. The input to our algorithm can be feature vectors, pairwise distances, or pairwise similarities. The learned status matrix can then be used for retrieval, clustering, andclassification.
VARIABLEFEATURES: HIGHLY VARIABLE FEATURES IN SEURATOBJECT In SeuratObject: Data Structures for Single Cell Data. Description Usage Arguments Value Examples. View source: R/generics.R. Description. Get and set variable feature information for an Assay object.HVFInfo and VariableFeatures utilize generally variable features, while SVFInfo and SpatiallyVariableFeatures are restricted to spatially variable features . Usage EXTREMEVALUES: AN R PACKAGE FOR OUTLIER DETECTION IN This package offers outlier detection and plot functions for univariate data. The package is the implementation of the outlier detection methods introduced in the reference below. Briefly, the methods work as follows. Using a subset of the data, the parameters for a model distribution are estimated using regression of the sorted data on their QQ-plot positions. A value in the data is an XJSUN1221/TINYARRAY: SIMPLIFY GEO AND TCGA ANALYSIS AND Simplify geo and tcga analysis and plots. box_surv: box_surv cor.full: cor.test for all varibles cor.one: cor.test for one varible with all varibles double_enrich: draw enrichment bar plots for both up and down genes draw_boxplot: draw boxplot for expression draw_heatmap: draw a heatmap plot draw_heatmap2: draw heatmap plots draw_pca: draw PCA plots draw_venn: draw a venn plot SEMPLOT: PATH DIAGRAMS AND VISUAL ANALYSIS OF VARIOUS SEM cvregsemplot: Bridge between cv_regsem output and sempaths edits: Functions to facilitate editting 'semPlotModel' objects. Imin: Helper function to substract matrix from identity matrix and lisrelModel: Construct SEM model using LISREL matrix specification. modelMatrices: Extract SEM model matrices ramModel: Construct SEM model using RAM matrix specification. NLSWORK: NATIONAL LONGITUDINAL SURVEY OF YOUNG WORKINGSEE MORE ONRDRR.IO
GUYOT.METHOD: GO FROM KM CURVE DATA FROM PUBLISHED FIGURES This function is a simple adaptation of code given by Guyot et al. add_baseline_column: add_baseline_column check_connected: check_connected guyot.method: Go from KM curve data from published figures into hazard_plot: hazard_plot hazard_table: hazard_table mrcc_small: A dataset containing survival times of individuals undergoing prep_all_hazards: prep_all_hazards GPA2: GPA2 IN WOOLDRIDGE: 111 DATA SETS FROM "INTRODUCTORY Format. A data.frame with 4137 observations on 12 variables: sat: combined SAT score tothrs: total hours through fall semest colgpa: GPA after fall semester athlete: =1 if athlete verbmath: verbal/math SAT score hsize: size grad. class, 100s hsrank: rank in grad. class hsperc: high school percentile, from top female: =1 if female white: =1 if white black: =1 if black META: GENERAL PACKAGE FOR META-ANALYSIS VERSION 4.18-1 amlodipine: Amlodipine for Work Capacity as.data.frame.meta: Additional functions for objects of class meta baujat.meta: Baujat plot to explore heterogeneity in meta-analysis bubble.metareg: Bubble plot to display the result of a meta-regression ci: Calculation of confidence intervals (based on normal cisapride: Cisapride inNon-Ulcer Dispepsia
POWDR: FULL PATTERN SUMMATION OF X-RAY POWDER DIFFRACTION afps: Automated full pattern summation afps.powdRlib: Automated full pattern summation bkg: Fit a background to XRPD data fps: Full pattern summation fps.powdRlib: Full pattern summation minerals: An example powdRlib reference library minerals_phases: A table of associated data for the minerals_xrd table, which minerals_regroup_structure: Example regrouping structure for the DINCERTI/CEA SOURCE: TESTS/TESTTHAT/TEST-PARAMS_MLOGIT_LIST.R absorbing: Absorbing states apply_rr: Apply relative risks to transition probability matrices as_array3: Convert between 2D tabular objects and 3D arrays as.data.table.tparams_transprobs: Coerce to 'data.table' as_pfs_os: Convert multi-state data to PFS and OS data autoplot.stateprobs: Plot state probabilities autoplot.survival: Plotsurvival curves
ROWR: ROW-BASED FUNCTIONS FOR R OBJECTS VERSION 1.1.3 FROM rowr: Row-Based Functions for R Objects. Provides utilities which interact with all R objects as if they were arranged in rows. It allows more consistent and predictable output to common functions, and generalizes a number of utility functions to to be failsafe with any number and type of input objects. SEMPLOT: PATH DIAGRAMS AND VISUAL ANALYSIS OF VARIOUS SEM cvregsemplot: Bridge between cv_regsem output and sempaths edits: Functions to facilitate editting 'semPlotModel' objects. Imin: Helper function to substract matrix from identity matrix and lisrelModel: Construct SEM model using LISREL matrix specification. modelMatrices: Extract SEM model matrices ramModel: Construct SEM model using RAM matrix specification. LOGFC: CALCULATE LOG-FOLD CHANGES FROM HURDLE MODEL Details. The log-fold change is defined as follows. For each gene, let u(x) be the expected value of the continuous component, given a covariate x and the estimated coefficients coefC, ie, u(x)= crossprod(x, coefC).Likewise, Let v(x)= 1/(1+exp(-crossprod(coefD, x))) be the expected value of the discrete component. The log fold change from contrast0 to contrast1 is defined as DECONTX: CONTAMINATION ESTIMATION WITH DECONTX IN CELDA x: A numeric matrix of counts or a SingleCellExperiment with the matrix located in the assay slot under assayName.Cells in each batch will be subsetted and converted to a sparse matrix of class dgCMatrix from package Matrix before analysis. This object should onlyRDRR.IO
rdrr.io
GENLASSO: PATH ALGORITHM FOR GENERALIZED LASSO PROBLEMS genlasso: Path Algorithm for Generalized Lasso Problems. Computes the solution path for generalized lasso problems. Important use cases are the fused lasso over an arbitrary graph, and trend fitting of any given polynomial order. Specialized implementations for the latter two subproblems are given to improve stability and speed. ZONGYF02/INORMUS: README.MD are_boxes_invalid: Helper to determine if coding boxes are valid check_admfrom_ihunits: The time from injury to hospital admission should be within check_condate_hspdate: Check that consent date should be 0 - 30 days after hospital check_condate_injdate: Check that consent date should be on the same day, or after check_form2.1_box5: Filters out invalid rows for box 5 of form2.1 CIT: CAUSAL INFERENCE TEST VERSION 2.3.1 FROM CRANAUTHOR: JOSHUAMILLSTEIN
The hypothesis test generates a p-value or permutation-based FDR value with confidence intervals to quantify uncertainty in the causal inference. The outcome can be represented by either a continuous or binary variable, the potential mediator is continuous, and the instrumental variable can be continuous or binary and is not limitedto a single
HTMLTOOLS: TOOLS FOR HTML VERSION 0.5.1.1 FROM CRAN Tools for HTML generation and output. as.tags: Convert a value to tags browsable: Make an HTML object browsable builder: HTML Builder Functions capturePlot: Capture a plot as a saved file copyDependencyToDir: Copy an HTML dependency to a directory css: CSS string helper defaultPngDevice: Determine the best PNG device for your system findDependencies: Collect attached SNFTOOL: SIMILARITY NETWORK FUSION VERSION 2.3.0 FROM CRAN SNFtool: Similarity Network Fusion. Similarity Network Fusion takes multiple views of a network and fuses them together to construct an overall status matrix. The input to our algorithm can be feature vectors, pairwise distances, or pairwise similarities. The learned status matrix can then be used for retrieval, clustering, andclassification.
VARIABLEFEATURES: HIGHLY VARIABLE FEATURES IN SEURATOBJECT In SeuratObject: Data Structures for Single Cell Data. Description Usage Arguments Value Examples. View source: R/generics.R. Description. Get and set variable feature information for an Assay object.HVFInfo and VariableFeatures utilize generally variable features, while SVFInfo and SpatiallyVariableFeatures are restricted to spatially variable features . Usage EXTREMEVALUES: AN R PACKAGE FOR OUTLIER DETECTION IN This package offers outlier detection and plot functions for univariate data. The package is the implementation of the outlier detection methods introduced in the reference below. Briefly, the methods work as follows. Using a subset of the data, the parameters for a model distribution are estimated using regression of the sorted data on their QQ-plot positions. A value in the data is an XJSUN1221/TINYARRAY: SIMPLIFY GEO AND TCGA ANALYSIS AND Simplify geo and tcga analysis and plots. box_surv: box_surv cor.full: cor.test for all varibles cor.one: cor.test for one varible with all varibles double_enrich: draw enrichment bar plots for both up and down genes draw_boxplot: draw boxplot for expression draw_heatmap: draw a heatmap plot draw_heatmap2: draw heatmap plots draw_pca: draw PCA plots draw_venn: draw a venn plot SEMPLOT: PATH DIAGRAMS AND VISUAL ANALYSIS OF VARIOUS SEM cvregsemplot: Bridge between cv_regsem output and sempaths edits: Functions to facilitate editting 'semPlotModel' objects. Imin: Helper function to substract matrix from identity matrix and lisrelModel: Construct SEM model using LISREL matrix specification. modelMatrices: Extract SEM model matrices ramModel: Construct SEM model using RAM matrix specification. NLSWORK: NATIONAL LONGITUDINAL SURVEY OF YOUNG WORKINGSEE MORE ONRDRR.IO
GUYOT.METHOD: GO FROM KM CURVE DATA FROM PUBLISHED FIGURES This function is a simple adaptation of code given by Guyot et al. add_baseline_column: add_baseline_column check_connected: check_connected guyot.method: Go from KM curve data from published figures into hazard_plot: hazard_plot hazard_table: hazard_table mrcc_small: A dataset containing survival times of individuals undergoing prep_all_hazards: prep_all_hazards GPA2: GPA2 IN WOOLDRIDGE: 111 DATA SETS FROM "INTRODUCTORY Format. A data.frame with 4137 observations on 12 variables: sat: combined SAT score tothrs: total hours through fall semest colgpa: GPA after fall semester athlete: =1 if athlete verbmath: verbal/math SAT score hsize: size grad. class, 100s hsrank: rank in grad. class hsperc: high school percentile, from top female: =1 if female white: =1 if white black: =1 if black CIT: CAUSAL INFERENCE TEST VERSION 2.3.1 FROM CRANAUTHOR: JOSHUAMILLSTEIN
The hypothesis test generates a p-value or permutation-based FDR value with confidence intervals to quantify uncertainty in the causal inference. The outcome can be represented by either a continuous or binary variable, the potential mediator is continuous, and the instrumental variable can be continuous or binary and is not limitedto a single
HTMLTOOLS: TOOLS FOR HTML VERSION 0.5.1.1 FROM CRAN Tools for HTML generation and output. as.tags: Convert a value to tags browsable: Make an HTML object browsable builder: HTML Builder Functions capturePlot: Capture a plot as a saved file copyDependencyToDir: Copy an HTML dependency to a directory css: CSS string helper defaultPngDevice: Determine the best PNG device for your system findDependencies: Collect attached SNFTOOL: SIMILARITY NETWORK FUSION VERSION 2.3.0 FROM CRAN SNFtool: Similarity Network Fusion. Similarity Network Fusion takes multiple views of a network and fuses them together to construct an overall status matrix. The input to our algorithm can be feature vectors, pairwise distances, or pairwise similarities. The learned status matrix can then be used for retrieval, clustering, andclassification.
VARIABLEFEATURES: HIGHLY VARIABLE FEATURES IN SEURATOBJECT In SeuratObject: Data Structures for Single Cell Data. Description Usage Arguments Value Examples. View source: R/generics.R. Description. Get and set variable feature information for an Assay object.HVFInfo and VariableFeatures utilize generally variable features, while SVFInfo and SpatiallyVariableFeatures are restricted to spatially variable features . Usage EXTREMEVALUES: AN R PACKAGE FOR OUTLIER DETECTION IN This package offers outlier detection and plot functions for univariate data. The package is the implementation of the outlier detection methods introduced in the reference below. Briefly, the methods work as follows. Using a subset of the data, the parameters for a model distribution are estimated using regression of the sorted data on their QQ-plot positions. A value in the data is an XJSUN1221/TINYARRAY: SIMPLIFY GEO AND TCGA ANALYSIS AND Simplify geo and tcga analysis and plots. box_surv: box_surv cor.full: cor.test for all varibles cor.one: cor.test for one varible with all varibles double_enrich: draw enrichment bar plots for both up and down genes draw_boxplot: draw boxplot for expression draw_heatmap: draw a heatmap plot draw_heatmap2: draw heatmap plots draw_pca: draw PCA plots draw_venn: draw a venn plot SEMPLOT: PATH DIAGRAMS AND VISUAL ANALYSIS OF VARIOUS SEM cvregsemplot: Bridge between cv_regsem output and sempaths edits: Functions to facilitate editting 'semPlotModel' objects. Imin: Helper function to substract matrix from identity matrix and lisrelModel: Construct SEM model using LISREL matrix specification. modelMatrices: Extract SEM model matrices ramModel: Construct SEM model using RAM matrix specification. NLSWORK: NATIONAL LONGITUDINAL SURVEY OF YOUNG WORKINGSEE MORE ONRDRR.IO
GUYOT.METHOD: GO FROM KM CURVE DATA FROM PUBLISHED FIGURES This function is a simple adaptation of code given by Guyot et al. add_baseline_column: add_baseline_column check_connected: check_connected guyot.method: Go from KM curve data from published figures into hazard_plot: hazard_plot hazard_table: hazard_table mrcc_small: A dataset containing survival times of individuals undergoing prep_all_hazards: prep_all_hazards GPA2: GPA2 IN WOOLDRIDGE: 111 DATA SETS FROM "INTRODUCTORY Format. A data.frame with 4137 observations on 12 variables: sat: combined SAT score tothrs: total hours through fall semest colgpa: GPA after fall semester athlete: =1 if athlete verbmath: verbal/math SAT score hsize: size grad. class, 100s hsrank: rank in grad. class hsperc: high school percentile, from top female: =1 if female white: =1 if white black: =1 if black META: GENERAL PACKAGE FOR META-ANALYSIS VERSION 4.18-1 amlodipine: Amlodipine for Work Capacity as.data.frame.meta: Additional functions for objects of class meta baujat.meta: Baujat plot to explore heterogeneity in meta-analysis bubble.metareg: Bubble plot to display the result of a meta-regression ci: Calculation of confidence intervals (based on normal cisapride: Cisapride inNon-Ulcer Dispepsia
POWDR: FULL PATTERN SUMMATION OF X-RAY POWDER DIFFRACTION afps: Automated full pattern summation afps.powdRlib: Automated full pattern summation bkg: Fit a background to XRPD data fps: Full pattern summation fps.powdRlib: Full pattern summation minerals: An example powdRlib reference library minerals_phases: A table of associated data for the minerals_xrd table, which minerals_regroup_structure: Example regrouping structure for the DINCERTI/CEA SOURCE: TESTS/TESTTHAT/TEST-PARAMS_MLOGIT_LIST.R absorbing: Absorbing states apply_rr: Apply relative risks to transition probability matrices as_array3: Convert between 2D tabular objects and 3D arrays as.data.table.tparams_transprobs: Coerce to 'data.table' as_pfs_os: Convert multi-state data to PFS and OS data autoplot.stateprobs: Plot state probabilities autoplot.survival: Plotsurvival curves
ROWR: ROW-BASED FUNCTIONS FOR R OBJECTS VERSION 1.1.3 FROM rowr: Row-Based Functions for R Objects. Provides utilities which interact with all R objects as if they were arranged in rows. It allows more consistent and predictable output to common functions, and generalizes a number of utility functions to to be failsafe with any number and type of input objects. SEMPLOT: PATH DIAGRAMS AND VISUAL ANALYSIS OF VARIOUS SEM cvregsemplot: Bridge between cv_regsem output and sempaths edits: Functions to facilitate editting 'semPlotModel' objects. Imin: Helper function to substract matrix from identity matrix and lisrelModel: Construct SEM model using LISREL matrix specification. modelMatrices: Extract SEM model matrices ramModel: Construct SEM model using RAM matrix specification. LOGFC: CALCULATE LOG-FOLD CHANGES FROM HURDLE MODEL Details. The log-fold change is defined as follows. For each gene, let u(x) be the expected value of the continuous component, given a covariate x and the estimated coefficients coefC, ie, u(x)= crossprod(x, coefC).Likewise, Let v(x)= 1/(1+exp(-crossprod(coefD, x))) be the expected value of the discrete component. The log fold change from contrast0 to contrast1 is defined as DECONTX: CONTAMINATION ESTIMATION WITH DECONTX IN CELDA x: A numeric matrix of counts or a SingleCellExperiment with the matrix located in the assay slot under assayName.Cells in each batch will be subsetted and converted to a sparse matrix of class dgCMatrix from package Matrix before analysis. This object should onlyRDRR.IO
rdrr.io
GENLASSO: PATH ALGORITHM FOR GENERALIZED LASSO PROBLEMS genlasso: Path Algorithm for Generalized Lasso Problems. Computes the solution path for generalized lasso problems. Important use cases are the fused lasso over an arbitrary graph, and trend fitting of any given polynomial order. Specialized implementations for the latter two subproblems are given to improve stability and speed. ZONGYF02/INORMUS: README.MD are_boxes_invalid: Helper to determine if coding boxes are valid check_admfrom_ihunits: The time from injury to hospital admission should be within check_condate_hspdate: Check that consent date should be 0 - 30 days after hospital check_condate_injdate: Check that consent date should be on the same day, or after check_form2.1_box5: Filters out invalid rows for box 5 of form2.1 CIT: CAUSAL INFERENCE TEST VERSION 2.3.1 FROM CRANAUTHOR: JOSHUAMILLSTEIN
The hypothesis test generates a p-value or permutation-based FDR value with confidence intervals to quantify uncertainty in the causal inference. The outcome can be represented by either a continuous or binary variable, the potential mediator is continuous, and the instrumental variable can be continuous or binary and is not limitedto a single
HTMLTOOLS: TOOLS FOR HTML VERSION 0.5.1.1 FROM CRAN Tools for HTML generation and output. as.tags: Convert a value to tags browsable: Make an HTML object browsable builder: HTML Builder Functions capturePlot: Capture a plot as a saved file copyDependencyToDir: Copy an HTML dependency to a directory css: CSS string helper defaultPngDevice: Determine the best PNG device for your system findDependencies: Collect attached SNFTOOL: SIMILARITY NETWORK FUSION VERSION 2.3.0 FROM CRAN SNFtool: Similarity Network Fusion. Similarity Network Fusion takes multiple views of a network and fuses them together to construct an overall status matrix. The input to our algorithm can be feature vectors, pairwise distances, or pairwise similarities. The learned status matrix can then be used for retrieval, clustering, andclassification.
VARIABLEFEATURES: HIGHLY VARIABLE FEATURES IN SEURATOBJECT In SeuratObject: Data Structures for Single Cell Data. Description Usage Arguments Value Examples. View source: R/generics.R. Description. Get and set variable feature information for an Assay object.HVFInfo and VariableFeatures utilize generally variable features, while SVFInfo and SpatiallyVariableFeatures are restricted to spatially variable features . Usage EXTREMEVALUES: AN R PACKAGE FOR OUTLIER DETECTION IN This package offers outlier detection and plot functions for univariate data. The package is the implementation of the outlier detection methods introduced in the reference below. Briefly, the methods work as follows. Using a subset of the data, the parameters for a model distribution are estimated using regression of the sorted data on their QQ-plot positions. A value in the data is an XJSUN1221/TINYARRAY: SIMPLIFY GEO AND TCGA ANALYSIS AND Simplify geo and tcga analysis and plots. box_surv: box_surv cor.full: cor.test for all varibles cor.one: cor.test for one varible with all varibles double_enrich: draw enrichment bar plots for both up and down genes draw_boxplot: draw boxplot for expression draw_heatmap: draw a heatmap plot draw_heatmap2: draw heatmap plots draw_pca: draw PCA plots draw_venn: draw a venn plot SEMPLOT: PATH DIAGRAMS AND VISUAL ANALYSIS OF VARIOUS SEM cvregsemplot: Bridge between cv_regsem output and sempaths edits: Functions to facilitate editting 'semPlotModel' objects. Imin: Helper function to substract matrix from identity matrix and lisrelModel: Construct SEM model using LISREL matrix specification. modelMatrices: Extract SEM model matrices ramModel: Construct SEM model using RAM matrix specification. NLSWORK: NATIONAL LONGITUDINAL SURVEY OF YOUNG WORKINGSEE MORE ONRDRR.IO
GUYOT.METHOD: GO FROM KM CURVE DATA FROM PUBLISHED FIGURES This function is a simple adaptation of code given by Guyot et al. add_baseline_column: add_baseline_column check_connected: check_connected guyot.method: Go from KM curve data from published figures into hazard_plot: hazard_plot hazard_table: hazard_table mrcc_small: A dataset containing survival times of individuals undergoing prep_all_hazards: prep_all_hazards GPA2: GPA2 IN WOOLDRIDGE: 111 DATA SETS FROM "INTRODUCTORY Format. A data.frame with 4137 observations on 12 variables: sat: combined SAT score tothrs: total hours through fall semest colgpa: GPA after fall semester athlete: =1 if athlete verbmath: verbal/math SAT score hsize: size grad. class, 100s hsrank: rank in grad. class hsperc: high school percentile, from top female: =1 if female white: =1 if white black: =1 if black CIT: CAUSAL INFERENCE TEST VERSION 2.3.1 FROM CRANAUTHOR: JOSHUAMILLSTEIN
The hypothesis test generates a p-value or permutation-based FDR value with confidence intervals to quantify uncertainty in the causal inference. The outcome can be represented by either a continuous or binary variable, the potential mediator is continuous, and the instrumental variable can be continuous or binary and is not limitedto a single
HTMLTOOLS: TOOLS FOR HTML VERSION 0.5.1.1 FROM CRAN Tools for HTML generation and output. as.tags: Convert a value to tags browsable: Make an HTML object browsable builder: HTML Builder Functions capturePlot: Capture a plot as a saved file copyDependencyToDir: Copy an HTML dependency to a directory css: CSS string helper defaultPngDevice: Determine the best PNG device for your system findDependencies: Collect attached SNFTOOL: SIMILARITY NETWORK FUSION VERSION 2.3.0 FROM CRAN SNFtool: Similarity Network Fusion. Similarity Network Fusion takes multiple views of a network and fuses them together to construct an overall status matrix. The input to our algorithm can be feature vectors, pairwise distances, or pairwise similarities. The learned status matrix can then be used for retrieval, clustering, andclassification.
VARIABLEFEATURES: HIGHLY VARIABLE FEATURES IN SEURATOBJECT In SeuratObject: Data Structures for Single Cell Data. Description Usage Arguments Value Examples. View source: R/generics.R. Description. Get and set variable feature information for an Assay object.HVFInfo and VariableFeatures utilize generally variable features, while SVFInfo and SpatiallyVariableFeatures are restricted to spatially variable features . Usage EXTREMEVALUES: AN R PACKAGE FOR OUTLIER DETECTION IN This package offers outlier detection and plot functions for univariate data. The package is the implementation of the outlier detection methods introduced in the reference below. Briefly, the methods work as follows. Using a subset of the data, the parameters for a model distribution are estimated using regression of the sorted data on their QQ-plot positions. A value in the data is an XJSUN1221/TINYARRAY: SIMPLIFY GEO AND TCGA ANALYSIS AND Simplify geo and tcga analysis and plots. box_surv: box_surv cor.full: cor.test for all varibles cor.one: cor.test for one varible with all varibles double_enrich: draw enrichment bar plots for both up and down genes draw_boxplot: draw boxplot for expression draw_heatmap: draw a heatmap plot draw_heatmap2: draw heatmap plots draw_pca: draw PCA plots draw_venn: draw a venn plot SEMPLOT: PATH DIAGRAMS AND VISUAL ANALYSIS OF VARIOUS SEM cvregsemplot: Bridge between cv_regsem output and sempaths edits: Functions to facilitate editting 'semPlotModel' objects. Imin: Helper function to substract matrix from identity matrix and lisrelModel: Construct SEM model using LISREL matrix specification. modelMatrices: Extract SEM model matrices ramModel: Construct SEM model using RAM matrix specification. NLSWORK: NATIONAL LONGITUDINAL SURVEY OF YOUNG WORKINGSEE MORE ONRDRR.IO
GUYOT.METHOD: GO FROM KM CURVE DATA FROM PUBLISHED FIGURES This function is a simple adaptation of code given by Guyot et al. add_baseline_column: add_baseline_column check_connected: check_connected guyot.method: Go from KM curve data from published figures into hazard_plot: hazard_plot hazard_table: hazard_table mrcc_small: A dataset containing survival times of individuals undergoing prep_all_hazards: prep_all_hazards GPA2: GPA2 IN WOOLDRIDGE: 111 DATA SETS FROM "INTRODUCTORY Format. A data.frame with 4137 observations on 12 variables: sat: combined SAT score tothrs: total hours through fall semest colgpa: GPA after fall semester athlete: =1 if athlete verbmath: verbal/math SAT score hsize: size grad. class, 100s hsrank: rank in grad. class hsperc: high school percentile, from top female: =1 if female white: =1 if white black: =1 if black META: GENERAL PACKAGE FOR META-ANALYSIS VERSION 4.18-1 amlodipine: Amlodipine for Work Capacity as.data.frame.meta: Additional functions for objects of class meta baujat.meta: Baujat plot to explore heterogeneity in meta-analysis bubble.metareg: Bubble plot to display the result of a meta-regression ci: Calculation of confidence intervals (based on normal cisapride: Cisapride inNon-Ulcer Dispepsia
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POWDR: FULL PATTERN SUMMATION OF X-RAY POWDER DIFFRACTION afps: Automated full pattern summation afps.powdRlib: Automated full pattern summation bkg: Fit a background to XRPD data fps: Full pattern summation fps.powdRlib: Full pattern summation minerals: An example powdRlib reference library minerals_phases: A table of associated data for the minerals_xrd table, which minerals_regroup_structure: Example regrouping structure for the ROWR: ROW-BASED FUNCTIONS FOR R OBJECTS VERSION 1.1.3 FROM rowr: Row-Based Functions for R Objects. Provides utilities which interact with all R objects as if they were arranged in rows. It allows more consistent and predictable output to common functions, and generalizes a number of utility functions to to be failsafe with any number and type of input objects. LOGFC: CALCULATE LOG-FOLD CHANGES FROM HURDLE MODEL Details. The log-fold change is defined as follows. For each gene, let u(x) be the expected value of the continuous component, given a covariate x and the estimated coefficients coefC, ie, u(x)= crossprod(x, coefC).Likewise, Let v(x)= 1/(1+exp(-crossprod(coefD, x))) be the expected value of the discrete component. The log fold change from contrast0 to contrast1 is defined as DINCERTI/CEA SOURCE: TESTS/TESTTHAT/TEST-PARAMS_MLOGIT_LIST.R absorbing: Absorbing states apply_rr: Apply relative risks to transition probability matrices as_array3: Convert between 2D tabular objects and 3D arrays as.data.table.tparams_transprobs: Coerce to 'data.table' as_pfs_os: Convert multi-state data to PFS and OS data autoplot.stateprobs: Plot state probabilities autoplot.survival: Plotsurvival curves
SEMPLOT: PATH DIAGRAMS AND VISUAL ANALYSIS OF VARIOUS SEM cvregsemplot: Bridge between cv_regsem output and sempaths edits: Functions to facilitate editting 'semPlotModel' objects. Imin: Helper function to substract matrix from identity matrix and lisrelModel: Construct SEM model using LISREL matrix specification. modelMatrices: Extract SEM model matrices ramModel: Construct SEM model using RAM matrix specification. DECONTX: CONTAMINATION ESTIMATION WITH DECONTX IN CELDA x: A numeric matrix of counts or a SingleCellExperiment with the matrix located in the assay slot under assayName.Cells in each batch will be subsetted and converted to a sparse matrix of class dgCMatrix from package Matrix before analysis. This object should only GENLASSO: PATH ALGORITHM FOR GENERALIZED LASSO PROBLEMS genlasso: Path Algorithm for Generalized Lasso Problems. Computes the solution path for generalized lasso problems. Important use cases are the fused lasso over an arbitrary graph, and trend fitting of any given polynomial order. Specialized implementations for the latter two subproblems are given to improve stability and speed. ZONGYF02/INORMUS: README.MD are_boxes_invalid: Helper to determine if coding boxes are valid check_admfrom_ihunits: The time from injury to hospital admission should be within check_condate_hspdate: Check that consent date should be 0 - 30 days after hospital check_condate_injdate: Check that consent date should be on the same day, or after check_form2.1_box5: Filters out invalid rows for box 5 of form2.1 CIT: CAUSAL INFERENCE TEST VERSION 2.3.1 FROM CRANAUTHOR: JOSHUAMILLSTEIN
The hypothesis test generates a p-value or permutation-based FDR value with confidence intervals to quantify uncertainty in the causal inference. The outcome can be represented by either a continuous or binary variable, the potential mediator is continuous, and the instrumental variable can be continuous or binary and is not limitedto a single
GENLASSO: PATH ALGORITHM FOR GENERALIZED LASSO PROBLEMS genlasso: Path Algorithm for Generalized Lasso Problems. Computes the solution path for generalized lasso problems. Important use cases are the fused lasso over an arbitrary graph, and trend fitting of any given polynomial order. Specialized implementations for the latter two subproblems are given to improve stability and speed. POWDR: FULL PATTERN SUMMATION OF X-RAY POWDER DIFFRACTION afps: Automated full pattern summation afps.powdRlib: Automated full pattern summation bkg: Fit a background to XRPD data fps: Full pattern summation fps.powdRlib: Full pattern summation minerals: An example powdRlib reference library minerals_phases: A table of associated data for the minerals_xrd table, which minerals_regroup_structure: Example regrouping structure for the WEATHERAUS: DAILY WEATHER OBSERVATIONS FROM MULTIPLESEE MORE ONRDRR.IO
EXTREMEVALUES: AN R PACKAGE FOR OUTLIER DETECTION IN This package offers outlier detection and plot functions for univariate data. The package is the implementation of the outlier detection methods introduced in the reference below. Briefly, the methods work as follows. Using a subset of the data, the parameters for a model distribution are estimated using regression of the sorted data on their QQ-plot positions. A value in the data is an RFE: BACKWARDS FEATURE SELECTION IN CARET: CLASSIFICATIONCARET LINEAR REGRESSIONR FEATURE SELECTIONRFE IN RRFE SVM IN RCARET AUCSVM RFECARET
x: A matrix or data frame of predictors for model training. This object must have unique column names. For the recipes method, x is a recipe object. options to pass to the model fitting function (ignoredin predict.rfe) y
PLGEM.OBSSTN: COMPUTATION OF OBSERVED PLGEM-STN STATISTICS data: an object of class ExpressionSet; see Details for important information on how the phenoData slot of this object will be interpreted by the function.. plgemFit: list; the output of function plgem.fit.. covariate: integer, numeric or character; specifies the covariate to be used to distinguish the various experimental conditions from one another.See Details for how to specify thecovariate.
REGISTER_GOOGLE: REGISTER A GOOGLE API IN GGMAP: SPATIAL bb2bbox: Convert a bb specification to a bbox specification calc_zoom: Calculate a zoom given a bounding box crime: Crime data file_drawer: Manage the ggmap file drawer. geocode: Geocode geom_leg: Single line segments with rounded ends get_cloudmademap: Get a CloudMade map. get_googlemap: Get a Google Map. get_map: Grab a map. get_navermap:Get a Naver Map
NLSWORK: NATIONAL LONGITUDINAL SURVEY OF YOUNG WORKINGSEE MORE ONRDRR.IO
GPA2: GPA2 IN WOOLDRIDGE: 111 DATA SETS FROM "INTRODUCTORY Format. A data.frame with 4137 observations on 12 variables: sat: combined SAT score tothrs: total hours through fall semest colgpa: GPA after fall semester athlete: =1 if athlete verbmath: verbal/math SAT score hsize: size grad. class, 100s hsrank: rank in grad. class hsperc: high school percentile, from top female: =1 if female white: =1 if white black: =1 if black CIT: CAUSAL INFERENCE TEST VERSION 2.3.1 FROM CRANAUTHOR: JOSHUAMILLSTEIN
The hypothesis test generates a p-value or permutation-based FDR value with confidence intervals to quantify uncertainty in the causal inference. The outcome can be represented by either a continuous or binary variable, the potential mediator is continuous, and the instrumental variable can be continuous or binary and is not limitedto a single
GENLASSO: PATH ALGORITHM FOR GENERALIZED LASSO PROBLEMS genlasso: Path Algorithm for Generalized Lasso Problems. Computes the solution path for generalized lasso problems. Important use cases are the fused lasso over an arbitrary graph, and trend fitting of any given polynomial order. Specialized implementations for the latter two subproblems are given to improve stability and speed. POWDR: FULL PATTERN SUMMATION OF X-RAY POWDER DIFFRACTION afps: Automated full pattern summation afps.powdRlib: Automated full pattern summation bkg: Fit a background to XRPD data fps: Full pattern summation fps.powdRlib: Full pattern summation minerals: An example powdRlib reference library minerals_phases: A table of associated data for the minerals_xrd table, which minerals_regroup_structure: Example regrouping structure for the WEATHERAUS: DAILY WEATHER OBSERVATIONS FROM MULTIPLESEE MORE ONRDRR.IO
EXTREMEVALUES: AN R PACKAGE FOR OUTLIER DETECTION IN This package offers outlier detection and plot functions for univariate data. The package is the implementation of the outlier detection methods introduced in the reference below. Briefly, the methods work as follows. Using a subset of the data, the parameters for a model distribution are estimated using regression of the sorted data on their QQ-plot positions. A value in the data is an RFE: BACKWARDS FEATURE SELECTION IN CARET: CLASSIFICATIONCARET LINEAR REGRESSIONR FEATURE SELECTIONRFE IN RRFE SVM IN RCARET AUCSVM RFECARET
x: A matrix or data frame of predictors for model training. This object must have unique column names. For the recipes method, x is a recipe object. options to pass to the model fitting function (ignoredin predict.rfe) y
PLGEM.OBSSTN: COMPUTATION OF OBSERVED PLGEM-STN STATISTICS data: an object of class ExpressionSet; see Details for important information on how the phenoData slot of this object will be interpreted by the function.. plgemFit: list; the output of function plgem.fit.. covariate: integer, numeric or character; specifies the covariate to be used to distinguish the various experimental conditions from one another.See Details for how to specify thecovariate.
REGISTER_GOOGLE: REGISTER A GOOGLE API IN GGMAP: SPATIAL bb2bbox: Convert a bb specification to a bbox specification calc_zoom: Calculate a zoom given a bounding box crime: Crime data file_drawer: Manage the ggmap file drawer. geocode: Geocode geom_leg: Single line segments with rounded ends get_cloudmademap: Get a CloudMade map. get_googlemap: Get a Google Map. get_map: Grab a map. get_navermap:Get a Naver Map
NLSWORK: NATIONAL LONGITUDINAL SURVEY OF YOUNG WORKINGSEE MORE ONRDRR.IO
GPA2: GPA2 IN WOOLDRIDGE: 111 DATA SETS FROM "INTRODUCTORY Format. A data.frame with 4137 observations on 12 variables: sat: combined SAT score tothrs: total hours through fall semest colgpa: GPA after fall semester athlete: =1 if athlete verbmath: verbal/math SAT score hsize: size grad. class, 100s hsrank: rank in grad. class hsperc: high school percentile, from top female: =1 if female white: =1 if white black: =1 if black META: GENERAL PACKAGE FOR META-ANALYSIS VERSION 4.18-1 amlodipine: Amlodipine for Work Capacity as.data.frame.meta: Additional functions for objects of class meta baujat.meta: Baujat plot to explore heterogeneity in meta-analysis bubble.metareg: Bubble plot to display the result of a meta-regression ci: Calculation of confidence intervals (based on normal cisapride: Cisapride inNon-Ulcer Dispepsia
EASYSTATS/MODELBASED SOURCE: TESTS/TESTTHAT/TEST describe_nonlinear: Describe the smooth term (for GAMs) or non-linear predictors dot-uniroot.all: Copied from rootSolve package estimate_contrasts: Estimate Marginal Contrasts estimate_expectation: Generates predictions from models estimate_grouplevel: Group-specific parameters of mixed models random effects estimate_means: Estimate Marginal Means (Model-based average at each factor MODELORIENTED/FAIRMODELS SOURCE: TESTS/TESTTHAT/TEST_PLOT adult: Adult dataset adult_test: Adult test dataset all_cutoffs: All cutoffs calculate_group_fairness_metrics: Calculate fairness metrics in groups ceteris_paribus_cutoff: Ceteris paribus cutoff choose_metric: Choose metric compas: Modified COMPAS dataset confusion_matrx: Confusion matrix disparate_impact_remover: Disparate impact remover expand_fairness_object: BUNNERVIKEN: BUNNERVIKEN RIVER IN SWEDEN IN SOR16/BDRC autoplot.gplm: Autoplot gplm fit autoplot.gplm0: Autoplot gplm0 fit autoplot.plm: Autoplot plm fit autoplot.plm0: Autoplot plm0 fit autoplot.tournament: Autoplot - Comparison of models in tournament bdrc: bdrc - Bayesian Discharge Rating Curves B_splines: B-splines in a generalized rating curve bunnerviken: Bunnerviken river in Sweden create_A: Linking unique water level measurements to TPP: ANALYZE THERMAL PROTEOME PROFILING (TPP) EXPERIMENTS analyze2DTPP: Analyze a 2D-TPP experiment analyzeTPPCCR: Analyze TPP-CCR experiment analyzeTPPTR: Analyze TPP-TR experiment hdacCCR_config: The configuration table to analyze hdacCCR_data. hdacCCR_data: TPP-CCR example dataset (replicates 1 and 2) hdacCCR_smallExample: Example subsets of a Panobinostat TPP-CCRdataset (replicates
POWDR: FULL PATTERN SUMMATION OF X-RAY POWDER DIFFRACTION afps: Automated full pattern summation afps.powdRlib: Automated full pattern summation bkg: Fit a background to XRPD data fps: Full pattern summation fps.powdRlib: Full pattern summation minerals: An example powdRlib reference library minerals_phases: A table of associated data for the minerals_xrd table, which minerals_regroup_structure: Example regrouping structure for the RCORR: MATRIX OF CORRELATIONS AND P-VALUES IN HMISC Details. Uses midranks in case of ties, as described by Hollander and Wolfe. P-values are approximated by using the t or F distributions.. Value. rcorr returns a list with elements r, the matrix of correlations, n the matrix of number of observations used in analyzing each pair of variables, and P, the asymptotic P-values.Pairs with fewer than 2 non-missing values have the r values set to NA. XJSUN1221/TINYARRAY: SIMPLIFY GEO AND TCGA ANALYSIS AND Simplify geo and tcga analysis and plots. box_surv: box_surv cor.full: cor.test for all varibles cor.one: cor.test for one varible with all varibles double_enrich: draw enrichment bar plots for both up and down genes draw_boxplot: draw boxplot for expression draw_heatmap: draw a heatmap plot draw_heatmap2: draw heatmap plots draw_pca: draw PCA plots draw_venn: draw a venn plot DECONTX: CONTAMINATION ESTIMATION WITH DECONTX IN CELDA x: A numeric matrix of counts or a SingleCellExperiment with the matrix located in the assay slot under assayName.Cells in each batch will be subsetted and converted to a sparse matrix of class dgCMatrix from package Matrix before analysis. This object should only DDSJOBERG/DCA SOURCE: R/NET_INTERVENTION_AVOIDED.R as_tibble.dca: Convert DCA Object to tibble dca: Perform Decision Curve Analysis dcurves-package: dcurves: Decision Curve Analysis df_binary: Simulated data with a binary outcome df_case_control: Simulated data with a case-control outcome df_surv: Simulated data with a survival outcome net_intervention_avoided: Add Net Interventions Avoided plot.dca: Plot DCA Object with ggplot META: GENERAL PACKAGE FOR META-ANALYSIS VERSION 4.18-1 amlodipine: Amlodipine for Work Capacity as.data.frame.meta: Additional functions for objects of class meta baujat.meta: Baujat plot to explore heterogeneity in meta-analysis bubble.metareg: Bubble plot to display the result of a meta-regression ci: Calculation of confidence intervals (based on normal cisapride: Cisapride inNon-Ulcer Dispepsia
CIT: CAUSAL INFERENCE TEST VERSION 2.3.1 FROM CRANAUTHOR: JOSHUAMILLSTEIN
cit.bp: Causal Inference Test for a Binary Outcome cit.cp: Causal Inference Test for a Continuous Outcome cit-package: Causal Inference Test fdr.cit: Omnibus FDR Values for CIT fdr.od: Permutation-Based FDR and Confidence Interval fdr.q.para: Parametric tail-area FDR Values, q-values fdr.q.perm: Nonparametric permutation-based tail-area FDR Values, iuq: Intersection/Union Q-Value ECDAT: DATA SETS FOR ECONOMETRICS VERSION 0.3-9 FROM CRAN Accident: Ship Accidents AccountantsAuditorsPct: Accountants and Auditors in the US 1850-2016 Airline: Cost for U.S. Airlines Airq: Air Quality for Californian Metropolitan Areas bankingCrises: Countries in Banking Crises Benefits: Unemployment of Blue Collar Workers Bids: Bids Received By U.S. Firms breaches: Cyber Security Breaches BudgetFood: Budget Share of Food for Spanish Households SEMPLOT: PATH DIAGRAMS AND VISUAL ANALYSIS OF VARIOUS SEM cvregsemplot: Bridge between cv_regsem output and sempaths edits: Functions to facilitate editting 'semPlotModel' objects. Imin: Helper function to substract matrix from identity matrix and lisrelModel: Construct SEM model using LISREL matrix specification. modelMatrices: Extract SEM model matrices ramModel: Construct SEM model using RAM matrix specification. REGISTER_GOOGLE: REGISTER A GOOGLE API IN GGMAP: SPATIAL bb2bbox: Convert a bb specification to a bbox specification calc_zoom: Calculate a zoom given a bounding box crime: Crime data file_drawer: Manage the ggmap file drawer. geocode: Geocode geom_leg: Single line segments with rounded ends get_cloudmademap: Get a CloudMade map. get_googlemap: Get a Google Map. get_map: Grab a map. get_navermap:Get a Naver Map
RUGARCH: UNIVARIATE GARCH MODELS VERSION 1.4-4 FROM CRAN ARFIMA, in-mean, external regressors and various GARCH flavors, with methods for fit, forecast, simulation, inference and plotting. RFE: BACKWARDS FEATURE SELECTION IN CARET: CLASSIFICATION x: A matrix or data frame of predictors for model training. This object must have unique column names. For the recipes method, x is a recipe object. options to pass to the model fitting function (ignoredin predict.rfe) y
CONVERT_TO_DATE: CONVERT MANY DATE AND DATETIME FORMATS AS add_totals_col: Append a totals column to a data.frame. add_totals_row: Append a totals row to a data.frame. adorn_crosstab: Add presentation formatting to a crosstabulation table. adorn_ns: Add underlying Ns to a tabyl displaying percentages. adorn_pct_formatting: Format a data.frame of decimals as percentages. adorn_percentages: Convert a data.frame of counts to percentages. MRCIEU/IEUGWASR DOCUMENTATION The MRCIEU/ieugwasr package contains the following man pages: afl2_chrpos afl2_list afl2_rsid api_query api_status associations batches batch_from_id check_access_token cor dot-data editcheck fill_n get_access_token get_query_content gwasinfo infer_ancestry ld_clump ld_clump_api ld_clump_local ld_matrix ld_matrix_local ld_reflookup legacy_ids logging_info phewas pipe revoke_access_token GGRARE: MAKE A RAREFACTION CURVE USING GGPLOT2 IN GAURAVSK convert_anacapa_to_phyloseq: Takes an site-abundance table from Anacapa, along with a convert_biom_to_taxon_table: Takes a biom table imported in using phyloseq::import_biom() custom_rarefaction: Rarefy a phyloseq object to a custom sample depth and with ggrare: Make a rarefaction curve using ggplot2 group_anacapa_by_taxonomy: Takes a site-abundance table from META: GENERAL PACKAGE FOR META-ANALYSIS VERSION 4.18-1 amlodipine: Amlodipine for Work Capacity as.data.frame.meta: Additional functions for objects of class meta baujat.meta: Baujat plot to explore heterogeneity in meta-analysis bubble.metareg: Bubble plot to display the result of a meta-regression ci: Calculation of confidence intervals (based on normal cisapride: Cisapride inNon-Ulcer Dispepsia
CIT: CAUSAL INFERENCE TEST VERSION 2.3.1 FROM CRANAUTHOR: JOSHUAMILLSTEIN
cit.bp: Causal Inference Test for a Binary Outcome cit.cp: Causal Inference Test for a Continuous Outcome cit-package: Causal Inference Test fdr.cit: Omnibus FDR Values for CIT fdr.od: Permutation-Based FDR and Confidence Interval fdr.q.para: Parametric tail-area FDR Values, q-values fdr.q.perm: Nonparametric permutation-based tail-area FDR Values, iuq: Intersection/Union Q-Value ECDAT: DATA SETS FOR ECONOMETRICS VERSION 0.3-9 FROM CRAN Accident: Ship Accidents AccountantsAuditorsPct: Accountants and Auditors in the US 1850-2016 Airline: Cost for U.S. Airlines Airq: Air Quality for Californian Metropolitan Areas bankingCrises: Countries in Banking Crises Benefits: Unemployment of Blue Collar Workers Bids: Bids Received By U.S. Firms breaches: Cyber Security Breaches BudgetFood: Budget Share of Food for Spanish Households SEMPLOT: PATH DIAGRAMS AND VISUAL ANALYSIS OF VARIOUS SEM cvregsemplot: Bridge between cv_regsem output and sempaths edits: Functions to facilitate editting 'semPlotModel' objects. Imin: Helper function to substract matrix from identity matrix and lisrelModel: Construct SEM model using LISREL matrix specification. modelMatrices: Extract SEM model matrices ramModel: Construct SEM model using RAM matrix specification. REGISTER_GOOGLE: REGISTER A GOOGLE API IN GGMAP: SPATIAL bb2bbox: Convert a bb specification to a bbox specification calc_zoom: Calculate a zoom given a bounding box crime: Crime data file_drawer: Manage the ggmap file drawer. geocode: Geocode geom_leg: Single line segments with rounded ends get_cloudmademap: Get a CloudMade map. get_googlemap: Get a Google Map. get_map: Grab a map. get_navermap:Get a Naver Map
RUGARCH: UNIVARIATE GARCH MODELS VERSION 1.4-4 FROM CRAN ARFIMA, in-mean, external regressors and various GARCH flavors, with methods for fit, forecast, simulation, inference and plotting. RFE: BACKWARDS FEATURE SELECTION IN CARET: CLASSIFICATION x: A matrix or data frame of predictors for model training. This object must have unique column names. For the recipes method, x is a recipe object. options to pass to the model fitting function (ignoredin predict.rfe) y
CONVERT_TO_DATE: CONVERT MANY DATE AND DATETIME FORMATS AS add_totals_col: Append a totals column to a data.frame. add_totals_row: Append a totals row to a data.frame. adorn_crosstab: Add presentation formatting to a crosstabulation table. adorn_ns: Add underlying Ns to a tabyl displaying percentages. adorn_pct_formatting: Format a data.frame of decimals as percentages. adorn_percentages: Convert a data.frame of counts to percentages. MRCIEU/IEUGWASR DOCUMENTATION The MRCIEU/ieugwasr package contains the following man pages: afl2_chrpos afl2_list afl2_rsid api_query api_status associations batches batch_from_id check_access_token cor dot-data editcheck fill_n get_access_token get_query_content gwasinfo infer_ancestry ld_clump ld_clump_api ld_clump_local ld_matrix ld_matrix_local ld_reflookup legacy_ids logging_info phewas pipe revoke_access_token GGRARE: MAKE A RAREFACTION CURVE USING GGPLOT2 IN GAURAVSK convert_anacapa_to_phyloseq: Takes an site-abundance table from Anacapa, along with a convert_biom_to_taxon_table: Takes a biom table imported in using phyloseq::import_biom() custom_rarefaction: Rarefy a phyloseq object to a custom sample depth and with ggrare: Make a rarefaction curve using ggplot2 group_anacapa_by_taxonomy: Takes a site-abundance table from SAVE: SAVE R OBJECTS save: Save R Objects Description Usage Arguments Details Compression Parallel compression Warnings Note See Also Examples Description. save writes an external representation of R objects to the specified file. The objects can be read back from the file at a later date by using the function load or attach (or data in some cases).. save.image() is just a short-cut for ‘save my current RCORR: MATRIX OF CORRELATIONS AND P-VALUES IN HMISC Details. Uses midranks in case of ties, as described by Hollander and Wolfe. P-values are approximated by using the t or F distributions.. Value. rcorr returns a list with elements r, the matrix of correlations, n the matrix of number of observations used in analyzing each pair of variables, and P, the asymptotic P-values.Pairs with fewer than 2 non-missing values have the r values set to NA. ECDAT: DATA SETS FOR ECONOMETRICS VERSION 0.3-9 FROM CRAN Accident: Ship Accidents AccountantsAuditorsPct: Accountants and Auditors in the US 1850-2016 Airline: Cost for U.S. Airlines Airq: Air Quality for Californian Metropolitan Areas bankingCrises: Countries in Banking Crises Benefits: Unemployment of Blue Collar Workers Bids: Bids Received By U.S. Firms breaches: Cyber Security Breaches BudgetFood: Budget Share of Food for Spanish Households RUGARCH: UNIVARIATE GARCH MODELS VERSION 1.4-4 FROM CRAN ARFIMA, in-mean, external regressors and various GARCH flavors, with methods for fit, forecast, simulation, inference and plotting. MRCIEU/IEUGWASR DOCUMENTATION The MRCIEU/ieugwasr package contains the following man pages: afl2_chrpos afl2_list afl2_rsid api_query api_status associations batches batch_from_id check_access_token cor dot-data editcheck fill_n get_access_token get_query_content gwasinfo infer_ancestry ld_clump ld_clump_api ld_clump_local ld_matrix ld_matrix_local ld_reflookup legacy_ids logging_info phewas pipe revoke_access_token PLOTMATH: MATHEMATICAL ANNOTATION IN R plotmath: Mathematical Annotation in R Description Details Other symbols References See Also Examples Description. If the text argument to one of the text-drawing functions (text, mtext, axis, legend) in R is an expression, the argument is interpreted as a mathematical expression and the output will be formatted according to TeX-like rules. Expressions can also be used for titles, subtitles CONVERT_TO_DATE: CONVERT MANY DATE AND DATETIME FORMATS AS add_totals_col: Append a totals column to a data.frame. add_totals_row: Append a totals row to a data.frame. adorn_crosstab: Add presentation formatting to a crosstabulation table. adorn_ns: Add underlying Ns to a tabyl displaying percentages. adorn_pct_formatting: Format a data.frame of decimals as percentages. adorn_percentages: Convert a data.frame of counts to percentages. GGRARE: MAKE A RAREFACTION CURVE USING GGPLOT2 IN GAURAVSK convert_anacapa_to_phyloseq: Takes an site-abundance table from Anacapa, along with a convert_biom_to_taxon_table: Takes a biom table imported in using phyloseq::import_biom() custom_rarefaction: Rarefy a phyloseq object to a custom sample depth and with ggrare: Make a rarefaction curve using ggplot2 group_anacapa_by_taxonomy: Takes a site-abundance table from ROMUNOV/AED: PACKAGE ACCOMPANYING 'MIXED EFFECTS MODELS Package accompanying 2009 book by Zuur et. al. (Mixed Effects Models and Extensions in Ecology with R). AED stands for "Analyzingecological data".
COHENSD: COHEN'S D IN LSR: COMPANION TO "LEARNING Details. The cohensD function calculates the Cohen's d measure of effect size in one of several different formats. The function is intended to be called in one of two different ways, mirroring the t.test function. That is, the first input argument x is a formula, then a command of the form cohensD(x = outcome~group, data = data.frame) is expected, whereas if x is a numeric variable, then a rdrr.io __Find an R package __ R language docs __ Run R in your browser __ R Notebooks__
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