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r-rcmdr
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public |
A platform-independent basic-statistics GUI (graphical user interface) for R, based on the tcltk package.
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2025-04-22 |
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r-rcmdrplugin.arnova
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public |
R Commander plug-in for repeated-measures and mixed-design ('split-plot') ANOVA. It adds a new menu entry for repeated measures that allows to deal with up to three within-subject factors and optionally with one or several between-subject factors. It also provides supplementary options to oneWayAnova() and multiWayAnova() functions, such as choice of ANOVA type, display of effect sizes and post hoc analysis for multiWayAnova().
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2025-04-22 |
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r-rcmdrmisc
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Various statistical, graphics, and data-management functions used by the Rcmdr package in the R Commander GUI for R.
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2025-04-22 |
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r-rchoice
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An implementation of simulated maximum likelihood method for the estimation of Binary (Probit and Logit), Ordered (Probit and Logit) and Poisson models with random parameters for cross-sectional and longitudinal data as presented in Sarrias (2016) <doi:10.18637/jss.v074.i10>.
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2025-04-22 |
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r-rcdk
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Allows the user to access functionality in the 'CDK', a Java framework for chemoinformatics. This allows the user to load molecules, evaluate fingerprints, calculate molecular descriptors and so on. In addition, the 'CDK' API allows the user to view structures in 2D.
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2025-04-22 |
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r-rcartocolor
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public |
Provides color schemes for maps and other graphics designed by 'CARTO' as described at <https://carto.com/carto-colors/>. It includes four types of palettes: aggregation, diverging, qualitative, and quantitative.
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2025-04-22 |
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r-rbounds
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Takes matched and unmatched data and calculates Rosenbaum bounds for the treatment effect. Calculates bounds for binary outcome data, Hodges-Lehmann point estimates, Wilcoxon signed-rank test for matched data and matched IV estimators, Wilcoxon sum rank test, and for data with multiple matched controls. The sensitivity analysis methods in this package are documented in Rosenbaum (2002) Observational Studies, <doi:10.1007/978-1-4757-3692-2>, Springer-Verlag.
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2025-04-22 |
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r-rbiascorrection
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public |
Implementation of the algorithms (with minor modifications) to correct bias in quantitative DNA methylation analyses as described by Moskalev et al. (2011) <doi:10.1093/nar/gkr213>. Publication: Kapsner et al. (2021) <doi:10.1002/ijc.33681>.
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2025-04-22 |
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r-rbayesianoptimization
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public |
A Pure R implementation of Bayesian Global Optimization with Gaussian Processes.
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2025-04-22 |
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r-rbcb
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public |
The Brazilian Central Bank API delivers many datasets which regard economic activity, regional economy, international economy, public finances, credit indicators and many more. For more information please see <http://dadosabertos.bcb.gov.br/>. These datasets can be accessed through 'rbcb' functions and can be obtained in different data structures common to R ('tibble', 'data.frame', 'xts', ...).
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2025-04-22 |
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r-rathena
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public |
Designed to be compatible with the R package 'DBI' (Database Interface) when connecting to Amazon Web Service ('AWS') Athena <https://aws.amazon.com/athena/>. To do this 'Python' 'Boto3' Software Development Kit ('SDK') <https://boto3.amazonaws.com/v1/documentation/api/latest/index.html> is used as a driver.
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2025-04-22 |
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r-rattle
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public |
The R Analytic Tool To Learn Easily (Rattle) provides a collection of utilities functions for the data scientist. A Gnome (RGtk2) based graphical interface is included with the aim to provide a simple and intuitive introduction to R for data science, allowing a user to quickly load data from a CSV file (or via ODBC), transform and explore the data, build and evaluate models, and export models as PMML (predictive modelling markup language) or as scores. A key aspect of the GUI is that all R commands are logged and commented through the log tab. This can be saved as a standalone R script file and as an aid for the user to learn R or to copy-and-paste directly into R itself. Note that RGtk2 and cairoDevice have been archived on CRAN. See <https://rattle.togaware.com> for installation instructions.
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2025-04-22 |
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r-rapportools
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Helper functions that act as wrappers to more advanced statistical methods with the advantage of having sane defaults for quick reporting.
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2025-04-22 |
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r-rapidoc
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public |
A collection of 'HTML', 'JavaScript', 'CSS' and fonts assets that generate 'RapiDoc' documentation from an 'OpenAPI' Specification: <https://mrin9.github.io/RapiDoc/>.
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2025-04-22 |
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r-rangemodelmetadata
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public |
Range Modeling Metadata Standards (RMMS) address three challenges: they (i) are designed for convenience to encourage use, (ii) accommodate a wide variety of applications, and (iii) are extensible to allow the community of range modelers to steer it as needed. RMMS are based on a data dictionary that specifies a hierarchical structure to catalog different aspects of the range modeling process. The dictionary balances a constrained, minimalist vocabulary to improve standardization with flexibility for users to provide their own values. Merow et al. (2019) <DOI:10.1111/geb.12993> describe the standards in more detail. Note that users who prefer to use the R package 'ecospat' can obtain it from <https://github.com/ecospat/ecospat>.
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2025-04-22 |
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r-randvar
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Implements random variables by means of S4 classes and methods.
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2025-04-22 |
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r-randomnames
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public |
Function for generating random gender and ethnicity correct first and/or last names. Names are chosen proportionally based upon their probability of appearing in a large scale data base of real names.
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2025-04-22 |
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r-randomcolor
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Simple methods to generate attractive random colors. The random colors are from a wrapper of 'randomColor.js' <https://github.com/davidmerfield/randomColor>. In addition, it also generates optimally distinct colors based on k-means (inspired by 'IWantHue' <https://github.com/medialab/iwanthue>).
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2025-04-22 |
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r-randomforestexplainer
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public |
A set of tools to help explain which variables are most important in a random forests. Various variable importance measures are calculated and visualized in different settings in order to get an idea on how their importance changes depending on our criteria (Hemant Ishwaran and Udaya B. Kogalur and Eiran Z. Gorodeski and Andy J. Minn and Michael S. Lauer (2010) <doi:10.1198/jasa.2009.tm08622>, Leo Breiman (2001) <doi:10.1023/A:1010933404324>).
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2025-04-22 |
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r-ralger
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The goal of 'ralger' is to facilitate web scraping in R.
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2025-04-22 |
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r-rage
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public |
Functions for calculating life history metrics using matrix population models ('MPMs'). Described in Jones et al. (2021) <doi:10.1101/2021.04.26.441330>.
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2025-04-22 |
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r-r5r
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Rapid realistic routing on multimodal transport networks (walk, bike, public transport and car) using 'R5', the Rapid Realistic Routing on Real-world and Reimagined networks engine <https://github.com/conveyal/r5>. The package allows users to generate detailed routing analysis or calculate travel time matrices using seamless parallel computing on top of the R5 Java machine. While R5 is developed by Conveyal, the package r5r is independently developed by a team at the Institute for Applied Economic Research (Ipea) with contributions from collaborators. Apart from the documentation in this package, users will find additional information on R5 documentation at <https://docs.conveyal.com/>. Although we try to keep new releases of r5r in synchrony with R5, the development of R5 follows Conveyal's independent update process. Hence, users should confirm the R5 version implied by the Conveyal user manual (see <https://docs.conveyal.com/changelog>) corresponds with the R5 version that r5r depends on.
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2025-04-22 |
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r-r2mlm
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public |
Generates both total- and level-specific R-squared measures from Rights and Sterba’s (2019) <doi:10.1037/met0000184> framework of R-squared measures for multilevel models with random intercepts and/or slopes, which is based on a complete decomposition of variance. Additionally generates graphical representations of these R-squared measures to allow visualizing and interpreting all measures in the framework together as an integrated set. This framework subsumes 10 previously-developed R-squared measures for multilevel models as special cases of 5 measures from the framework, and it also includes several newly-developed measures. Measures in the framework can be used to compute R-squared differences when comparing multilevel models (following procedures in Rights & Sterba (2020) <doi:10.1080/00273171.2019.1660605>).
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2025-04-22 |
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r-r2rtf
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Create production-ready Rich Text Format (RTF) table and figure with flexible format.
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2025-04-22 |
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r-r2glmm
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The model R squared and semi-partial R squared for the linear and generalized linear mixed model (LMM and GLMM) are computed with confidence limits. The R squared measure from Edwards et.al (2008) <DOI:10.1002/sim.3429> is extended to the GLMM using penalized quasi-likelihood (PQL) estimation (see Jaeger et al. 2016 <DOI:10.1080/02664763.2016.1193725>). Three methods of computation are provided and described as follows. First, The Kenward-Roger approach. Due to some inconsistency between the 'pbkrtest' package and the 'glmmPQL' function, the Kenward-Roger approach in the 'r2glmm' package is limited to the LMM. Second, The method introduced by Nakagawa and Schielzeth (2013) <DOI:10.1111/j.2041-210x.2012.00261.x> and later extended by Johnson (2014) <DOI:10.1111/2041-210X.12225>. The 'r2glmm' package only computes marginal R squared for the LMM and does not generalize the statistic to the GLMM; however, confidence limits and semi-partial R squared for fixed effects are useful additions. Lastly, an approach using standardized generalized variance (SGV) can be used for covariance model selection. Package installation instructions can be found in the readme file.
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2025-04-22 |
