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Hmisc:Harrell Miscellaneous
Contains many functions useful for data analysis, high-level graphics, utility operations, functions for computing sample size and power, simulation, importing and annotating datasets, imputing missing values, advanced table making, variable clustering, character string manipulation, conversion of R objects to LaTeX and html code, recoding variables, caching, simplified parallel computing, encrypting and decrypting data using a safe workflow, general moving window statistical estimation, and assistance in interpreting principal component analysis.
Maintained by Frank E Harrell Jr. Last updated 5 hours ago.
58.7 match 210 stars 17.61 score 17k scripts 750 dependentstidyverse
ggplot2:Create Elegant Data Visualisations Using the Grammar of Graphics
A system for 'declaratively' creating graphics, based on "The Grammar of Graphics". You provide the data, tell 'ggplot2' how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details.
Maintained by Thomas Lin Pedersen. Last updated 9 days ago.
data-visualisationvisualisation
1.9 match 6.6k stars 25.10 score 645k scripts 7.5k dependentsgforge
Gmisc:Descriptive Statistics, Transition Plots, and More
Tools for making the descriptive "Table 1" used in medical articles, a transition plot for showing changes between categories (also known as a Sankey diagram), flow charts by extending the grid package, a method for variable selection based on the SVD, Bézier lines with arrows complementing the ones in the 'grid' package, and more.
Maintained by Max Gordon. Last updated 2 years ago.
3.6 match 50 stars 10.40 score 233 scripts 2 dependentsnjtierney
naniar:Data Structures, Summaries, and Visualisations for Missing Data
Missing values are ubiquitous in data and need to be explored and handled in the initial stages of analysis. 'naniar' provides data structures and functions that facilitate the plotting of missing values and examination of imputations. This allows missing data dependencies to be explored with minimal deviation from the common work patterns of 'ggplot2' and tidy data. The work is fully discussed at Tierney & Cook (2023) <doi:10.18637/jss.v105.i07>.
Maintained by Nicholas Tierney. Last updated 4 days ago.
data-visualisationggplot2missing-datamissingnesstidy-data
1.5 match 657 stars 15.63 score 5.1k scripts 9 dependentsjuba
questionr:Functions to Make Surveys Processing Easier
Set of functions to make the processing and analysis of surveys easier : interactive shiny apps and addins for data recoding, contingency tables, dataset metadata handling, and several convenience functions.
Maintained by Julien Barnier. Last updated 1 days ago.
1.7 match 83 stars 12.62 score 1.1k scripts 19 dependentslionel-
ggstance:Horizontal 'ggplot2' Components
A 'ggplot2' extension that provides flipped components: horizontal versions of 'Stats' and 'Geoms', and vertical versions of 'Positions'. This package is now superseded by 'ggplot2' itself which now has full native support for horizontal layouts. It remains available for backward compatibility.
Maintained by Lionel Henry. Last updated 10 months ago.
1.8 match 201 stars 10.95 score 1.0k scripts 5 dependentsandrewhooker
PopED:Population (and Individual) Optimal Experimental Design
Optimal experimental designs for both population and individual studies based on nonlinear mixed-effect models. Often this is based on a computation of the Fisher Information Matrix. This package was developed for pharmacometric problems, and examples and predefined models are available for these types of systems. The methods are described in Nyberg et al. (2012) <doi:10.1016/j.cmpb.2012.05.005>, and Foracchia et al. (2004) <doi:10.1016/S0169-2607(03)00073-7>.
Maintained by Andrew C. Hooker. Last updated 5 months ago.
nlmeoptimal-designpharmacodynamicspharmacokineticspharmacometricspkpdpopulationpopulation-model
1.7 match 33 stars 9.58 score 300 scripts 1 dependentsanimint
animint2:Animated Interactive Grammar of Graphics
Functions are provided for defining animated, interactive data visualizations in R code, and rendering on a web page. The 2018 Journal of Computational and Graphical Statistics paper, <doi:10.1080/10618600.2018.1513367> describes the concepts implemented.
Maintained by Toby Hocking. Last updated 27 days ago.
1.7 match 64 stars 8.87 score 173 scriptshenrikbengtsson
PSCBS:Analysis of Parent-Specific DNA Copy Numbers
Segmentation of allele-specific DNA copy number data and detection of regions with abnormal copy number within each parental chromosome. Both tumor-normal paired and tumor-only analyses are supported.
Maintained by Henrik Bengtsson. Last updated 1 years ago.
acghcopynumbervariantssnpmicroarrayonechanneltwochannelgenetics
1.5 match 7 stars 7.63 score 34 scripts 9 dependentsrmheiberger
HH:Statistical Analysis and Data Display: Heiberger and Holland
Support software for Statistical Analysis and Data Display (Second Edition, Springer, ISBN 978-1-4939-2121-8, 2015) and (First Edition, Springer, ISBN 0-387-40270-5, 2004) by Richard M. Heiberger and Burt Holland. This contemporary presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The second edition includes redesigned graphics and additional chapters. The authors emphasize how to construct and interpret graphs, discuss principles of graphical design, and show how accompanying traditional tabular results are used to confirm the visual impressions derived directly from the graphs. Many of the graphical formats are novel and appear here for the first time in print. All chapters have exercises. All functions introduced in the book are in the package. R code for all examples, both graphs and tables, in the book is included in the scripts directory of the package.
Maintained by Richard M. Heiberger. Last updated 1 months ago.
1.7 match 3 stars 6.42 score 752 scripts 5 dependentstirgit
missCompare:Intuitive Missing Data Imputation Framework
Offers a convenient pipeline to test and compare various missing data imputation algorithms on simulated and real data. These include simpler methods, such as mean and median imputation and random replacement, but also include more sophisticated algorithms already implemented in popular R packages, such as 'mi', described by Su et al. (2011) <doi:10.18637/jss.v045.i02>; 'mice', described by van Buuren and Groothuis-Oudshoorn (2011) <doi:10.18637/jss.v045.i03>; 'missForest', described by Stekhoven and Buhlmann (2012) <doi:10.1093/bioinformatics/btr597>; 'missMDA', described by Josse and Husson (2016) <doi:10.18637/jss.v070.i01>; and 'pcaMethods', described by Stacklies et al. (2007) <doi:10.1093/bioinformatics/btm069>. The central assumption behind 'missCompare' is that structurally different datasets (e.g. larger datasets with a large number of correlated variables vs. smaller datasets with non correlated variables) will benefit differently from different missing data imputation algorithms. 'missCompare' takes measurements of your dataset and sets up a sandbox to try a curated list of standard and sophisticated missing data imputation algorithms and compares them assuming custom missingness patterns. 'missCompare' will also impute your real-life dataset for you after the selection of the best performing algorithm in the simulations. The package also provides various post-imputation diagnostics and visualizations to help you assess imputation performance.
Maintained by Tibor V. Varga. Last updated 4 years ago.
comparisoncomparison-benchmarksimputationimputation-algorithmimputation-methodsimputationskolmogorov-smirnovmissingmissing-datamissing-data-imputationmissing-status-checkmissing-valuesmissingnesspost-imputation-diagnosticsrmse
1.7 match 39 stars 5.89 score 40 scriptsnutterb
labelVector:Label Attributes for Atomic Vectors
Labels are a common construct in statistical software providing a human readable description of a variable. While variable names are succinct, quick to type, and follow a language's naming conventions, labels may be more illustrative and may use plain text and spaces. R does not provide native support for labels. Some packages, however, have made this feature available. Most notably, the 'Hmisc' package provides labelling methods for a number of different object. Due to design decisions, these methods are not all exported, and so are unavailable for use in package development. The 'labelVector' package supports labels for atomic vectors in a light-weight design that is suitable for use in other packages.
Maintained by Benjamin Nutter. Last updated 3 years ago.
2.0 match 4.21 score 18 scripts 6 dependentslandroni
RcmdrPlugin.Export:Export R Output to LaTeX or HTML
Export Rcmdr output to LaTeX or HTML code. The plug-in was originally intended to facilitate exporting Rcmdr output to formats other than ASCII text and to provide R novices with an easy-to-use, easy-to-access reference on exporting R objects to formats suited for printed output. The package documentation contains several pointers on creating reports, either by using conventional word processors or LaTeX/LyX.
Maintained by Liviu Andronic. Last updated 9 years ago.
1.8 match 2.70 score 3 scripts