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r-ggridges
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Ridgeline plots provide a convenient way of visualizing changes in distributions over time or space. This package enables the creation of such plots in 'ggplot2'.
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2025-03-25 |
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r-ggcorrplot
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The 'ggcorrplot' package can be used to visualize easily a correlation matrix using 'ggplot2'. It provides a solution for reordering the correlation matrix and displays the significance level on the plot. It also includes a function for computing a matrix of correlation p-values.
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2025-03-25 |
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r-ggally
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The R package 'ggplot2' is a plotting system based on the grammar of graphics. 'GGally' extends 'ggplot2' by adding several functions to reduce the complexity of combining geometric objects with transformed data. Some of these functions include a pairwise plot matrix, a two group pairwise plot matrix, a parallel coordinates plot, a survival plot, and several functions to plot networks.
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2025-03-25 |
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r-doby
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Contains: 1) Facilities for working with grouped data: 'do' something to data stratified 'by' some variables. 2) LSmeans (least-squares means), general linear contrasts. 3) Miscellaneous other utilities.
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2025-03-25 |
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r-dbplyr
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A 'dplyr' back end for databases that allows you to work with remote database tables as if they are in-memory data frames. Basic features works with any database that has a 'DBI' back end; more advanced features require 'SQL' translation to be provided by the package author.
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2025-03-25 |
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r-dataexplorer
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Automated data exploration process for analytic tasks and predictive modeling, so that users could focus on understanding data and extracting insights. The package scans and analyzes each variable, and visualizes them with typical graphical techniques. Common data processing methods are also available to treat and format data.
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2025-03-25 |
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r-crosstalk
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Provides building blocks for allowing HTML widgets to communicate with each other, with Shiny or without (i.e. static .html files). Currently supports linked brushing and filtering.
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2025-03-25 |
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r-cowplot
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Some helpful extensions and modifications to the 'ggplot2' package. In particular, this package makes it easy to combine multiple 'ggplot2' plots into one and label them with letters, e.g. A, B, C, etc., as is often required for scientific publications. The package also provides a streamlined and clean theme that is used in the Wilke lab, hence the package name, which stands for Claus O. Wilke's plot package.
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2025-03-25 |
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r-tseries
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Time series analysis and computational finance.
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2025-03-25 |
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r-tidyr
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An evolution of 'reshape2'. It's designed specifically for data tidying (not general reshaping or aggregating) and works well with 'dplyr' data pipelines.
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2025-03-25 |
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r-sna
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A range of tools for social network analysis, including node and graph-level indices, structural distance and covariance methods, structural equivalence detection, network regression, random graph generation, and 2D/3D network visualization.
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2025-03-25 |
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r-rsghb
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Functions for estimating models using a Hierarchical Bayesian (HB) framework. The flexibility comes in allowing the user to specify the likelihood function directly instead of assuming predetermined model structures. Types of models that can be estimated with this code include the family of discrete choice models (Multinomial Logit, Mixed Logit, Nested Logit, Error Components Logit and Latent Class) as well ordered response models like ordered probit and ordered logit. In addition, the package allows for flexibility in specifying parameters as either fixed (non-varying across individuals) or random with continuous distributions. Parameter distributions supported include normal, positive/negative log-normal, positive/negative censored normal, and the Johnson SB distribution. Kenneth Train's Matlab and Gauss code for doing Hierarchical Bayesian estimation has served as the basis for a few of the functions included in this package. These Matlab/Gauss functions have been rewritten to be optimized within R. Considerable code has been added to increase the flexibility and usability of the code base. Train's original Gauss and Matlab code can be found here: <http://elsa.berkeley.edu/Software/abstracts/train1006mxlhb.html> See Train's chapter on HB in Discrete Choice with Simulation here: <http://elsa.berkeley.edu/books/choice2.html>; and his paper on using HB with non-normal distributions here: <http://eml.berkeley.edu//~train/trainsonnier.pdf>. The authors would also like to thank the invaluable contributions of Stephane Hess and the Choice Modelling Centre: <https://cmc.leeds.ac.uk/>.
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2025-03-25 |
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r-readxl
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Import excel files into R. Supports '.xls' via the embedded 'libxls' C library <https://github.com/libxls/libxls> and '.xlsx' via the embedded 'RapidXML' C++ library <http://rapidxml.sourceforge.net>. Works on Windows, Mac and Linux without external dependencies.
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2025-03-25 |
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r-networkdynamic
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Simple interface routines to facilitate the handling of network objects with complex intertemporal data. This is a part of the "statnet" suite of packages for network analysis.
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2025-03-25 |
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r-mnlogit
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Time and memory efficient estimation of multinomial logit models using maximum likelihood method. Numerical optimization performed by Newton-Raphson method using an optimized, parallel C++ library to achieve fast computation of Hessian matrices. Motivated by large scale multiclass classification problems in econometrics and machine learning.
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2025-03-25 |
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r-mets
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Implementation of various statistical models for multivariate event history data <doi:10.1007/s10985-013-9244-x>. Including multivariate cumulative incidence models <doi:10.1002/sim.6016>, and bivariate random effects probit models (Liability models) <doi:10.1016/j.csda.2015.01.014>. Also contains two-stage binomial modelling that can do pairwise odds-ratio dependence modelling based marginal logistic regression models. This is an alternative to the alternating logistic regression approach (ALR).
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2025-03-25 |
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r-ipred
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Improved predictive models by indirect classification and bagging for classification, regression and survival problems as well as resampling based estimators of prediction error.
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2025-03-25 |
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r-haven
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Import foreign statistical formats into R via the embedded 'ReadStat' C library, <https://github.com/WizardMac/ReadStat>.
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2025-03-25 |
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r-ggrepel
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Provides text and label geoms for 'ggplot2' that help to avoid overlapping text labels. Labels repel away from each other and away from the data points.
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2025-03-25 |
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r-fitarma
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Implements fast maximum likelihood algorithm for fitting ARMA time series. Uses S3 methods print, summary, fitted, residuals. Fast exact Gaussian ARMA simulation.
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2025-03-25 |
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r-ergm
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An integrated set of tools to analyze and simulate networks based on exponential-family random graph models (ERGMs). 'ergm' is a part of the Statnet suite of packages for network analysis.
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2025-03-25 |
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r-coin
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Conditional inference procedures for the general independence problem including two-sample, K-sample (non-parametric ANOVA), correlation, censored, ordered and multivariate problems.
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2025-03-25 |
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r-vars
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Estimation, lag selection, diagnostic testing, forecasting, causality analysis, forecast error variance decomposition and impulse response functions of VAR models and estimation of SVAR and SVEC models.
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2025-03-25 |
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r-truncreg
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Estimation of models for truncated Gaussian variables by maximum likelihood.
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2025-03-25 |
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r-sqldf
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The sqldf() function is typically passed a single argument which is an SQL select statement where the table names are ordinary R data frame names. sqldf() transparently sets up a database, imports the data frames into that database, performs the SQL select or other statement and returns the result using a heuristic to determine which class to assign to each column of the returned data frame. The sqldf() or read.csv.sql() functions can also be used to read filtered files into R even if the original files are larger than R itself can handle. 'RSQLite', 'RH2', 'RMySQL' and 'RPostgreSQL' backends are supported.
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2025-03-25 |
