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r-shinythemes
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public |
Themes for use with Shiny. Includes several Bootstrap themes from <http://bootswatch.com/>, which are packaged for use with Shiny applications.
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2025-03-25 |
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r-shinyjs
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public |
Perform common useful JavaScript operations in Shiny apps that will greatly improve your apps without having to know any JavaScript. Examples include: hiding an element, disabling an input, resetting an input back to its original value, delaying code execution by a few seconds, and many more useful functions for both the end user and the developer. 'shinyjs' can also be used to easily call your own custom JavaScript functions from R.
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2025-03-25 |
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r-readods
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public |
Import ODS (OpenDocument Spreadsheet) into R as a data frame. Also support writing data frame into ODS file.
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2025-03-25 |
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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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2025-03-25 |
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r-pglm
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public |
Estimation of panel models for glm-like models: this includes binomial models (logit and probit) count models (poisson and negbin) and ordered models (logit and probit).
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2025-03-25 |
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r-mi
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public |
The mi package provides functions for data manipulation, imputing missing values in an approximate Bayesian framework, diagnostics of the models used to generate the imputations, confidence-building mechanisms to validate some of the assumptions of the imputation algorithm, and functions to analyze multiply imputed data sets with the appropriate degree of sampling uncertainty.
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2025-03-25 |
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r-lmertest
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public |
Provides p-values in type I, II or III anova and summary tables for lmer model fits (cf. lme4) via Satterthwaite's degrees of freedom method. A Kenward-Roger method is also available via the pbkrtest package. Model selection methods include step, drop1 and anova-like tables for random effects (ranova). Methods for Least-Square means (LS-means) and tests of linear contrasts of fixed effects are also available.
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2025-03-25 |
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r-lfda
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public |
Functions for performing and visualizing Local Fisher Discriminant Analysis(LFDA), Kernel Fisher Discriminant Analysis(KLFDA), and Semi-supervised Local Fisher Discriminant Analysis(SELF).
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2025-03-25 |
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r-keras
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public |
Interface to 'Keras' <https://keras.io>, a high-level neural networks 'API'. 'Keras' was developed with a focus on enabling fast experimentation, supports both convolution based networks and recurrent networks (as well as combinations of the two), and runs seamlessly on both 'CPU' and 'GPU' devices.
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2025-03-25 |
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r-intergraph
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public |
Functions implemented in this package allow to coerce (i.e. convert) network data between classes provided by other R packages. Currently supported classes are those defined in packages: network and igraph.
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2025-03-25 |
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r-gutenbergr
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public |
Download and process public domain works in the Project Gutenberg collection <http://www.gutenberg.org/>. Includes metadata for all Project Gutenberg works, so that they can be searched and retrieved.
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2025-03-25 |
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r-gmnl
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public |
An implementation of maximum simulated likelihood method for the estimation of multinomial logit models with random coefficients. Specifically, it allows estimating models with continuous heterogeneity such as the mixed multinomial logit and the generalized multinomial logit. It also allows estimating models with discrete heterogeneity such as the latent class and the mixed-mixed multinomial logit model.
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2025-03-25 |
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r-ggstance
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public |
A 'ggplot2' extension that provides flipped components: horizontal versions of 'Stats' and 'Geoms', and vertical versions of 'Positions'.
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2025-03-25 |
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r-ggraptr
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public |
Intended for both technical and non-technical users to create interactive data visualizations through a web browser GUI without writing any code.
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2025-03-25 |
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r-ggdendro
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public |
This is a set of tools for dendrograms and tree plots using 'ggplot2'. The 'ggplot2' philosophy is to clearly separate data from the presentation. Unfortunately the plot method for dendrograms plots directly to a plot device without exposing the data. The 'ggdendro' package resolves this by making available functions that extract the dendrogram plot data. The package provides implementations for tree, rpart, as well as diana and agnes cluster diagrams.
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2025-03-25 |
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r-feisr
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public |
Provides the function feis() to estimate fixed effects individual slope (FEIS) models. The FEIS model constitutes a more general version of the often-used fixed effects (FE) panel model, as implemented in the package 'plm' by Croissant and Millo (2008) <doi:10.18637/jss.v027.i02>. In FEIS models, data are not only person "demeaned" like in conventional FE models, but "detrended" by the predicted individual slope of each person or group. Estimation is performed by applying least squares lm() to the transformed data. For more details on FEIS models see Bruederl and Ludwig (2015, ISBN:1446252442); Frees (2001) <doi:10.2307/3316008>; Polachek and Kim (1994) <doi:10.1016/0304-4076(94)90075-2>; Wooldridge (2010, ISBN:0262294354). To test consistency of conventional FE and random effects estimators against heterogeneous slopes, the package also provides the functions feistest() for an artificial regression test and bsfeistest() for a bootstrapped version of the Hausman test.
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2025-03-25 |
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r-egg
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public |
Miscellaneous functions to help customise 'ggplot2' objects. High-level functions are provided to post-process 'ggplot2' layouts and allow alignment between plot panels, as well as setting panel sizes to fixed values. Other functions include a custom 'geom', and helper functions to enforce symmetric scales or add tags to facetted plots.
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2025-03-25 |
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r-dtplyr
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public |
This implements the data table back-end for 'dplyr' so that you can seamlessly use data table and 'dplyr' together.
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2025-03-25 |
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r-dmwr
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public |
This package includes functions and data accompanying the book "Data Mining with R, learning with case studies" by Luis Torgo, CRC Press 2010.
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2025-03-25 |
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r-dharma
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public |
The 'DHARMa' package uses a simulation-based approach to create readily interpretable scaled (quantile) residuals for fitted (generalized) linear mixed models. Currently supported are linear and generalized linear (mixed) models from 'lme4' (classes 'lmerMod', 'glmerMod'), 'glmmTMB' and 'spaMM', generalized additive models ('gam' from 'mgcv'), 'glm' (including 'negbin' from 'MASS', but excluding quasi-distributions) and 'lm' model classes. Moreover, externally created simulations, e.g. posterior predictive simulations from Bayesian software such as 'JAGS', 'STAN', or 'BUGS' can be processed as well. The resulting residuals are standardized to values between 0 and 1 and can be interpreted as intuitively as residuals from a linear regression. The package also provides a number of plot and test functions for typical model misspecification problems, such as over/underdispersion, zero-inflation, and residual spatial and temporal autocorrelation.
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2025-03-25 |
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r-censreg
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public |
Maximum Likelihood estimation of censored regression (Tobit) models with cross-sectional and panel data.
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2025-03-25 |
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r-bs4dash
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public |
Make 'Bootstrap 4' dashboards. Use the full power of 'AdminLTE3', a dashboard template built on top of 'Bootstrap 4' <https://github.com/almasaeed2010/AdminLTE/tree/v3-dev>.
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2025-03-25 |
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r-argondash
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Create awesome 'Bootstrap 4' dashboards powered by 'Argon'. See more here <https://rinterface.github.io/argonDash/>.
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2025-03-25 |
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r-sirt
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public |
Supplementary functions for item response models aiming to complement existing R packages. The functionality includes among others multidimensional compensatory and noncompensatory IRT models (Reckase, 2009, <doi:10.1007/978-0-387-89976-3>), MCMC for hierarchical IRT models and testlet models (Fox, 2010, <doi:10.1007/978-1-4419-0742-4>), NOHARM (McDonald, 1982, <doi:10.1177/014662168200600402>), Rasch copula model (Braeken, 2011, <doi:10.1007/s11336-010-9190-4>; Schroeders, Robitzsch & Schipolowski, 2014, <doi:10.1111/jedm.12054>), faceted and hierarchical rater models (DeCarlo, Kim & Johnson, 2011, <doi:10.1111/j.1745-3984.2011.00143.x>), ordinal IRT model (ISOP; Scheiblechner, 1995, <doi:10.1007/BF02301417>), DETECT statistic (Stout, Habing, Douglas & Kim, 1996, <doi:10.1177/014662169602000403>), local structural equation modeling (LSEM; Hildebrandt, Luedtke, Robitzsch, Sommer & Wilhelm, 2016, <doi:10.1080/00273171.2016.1142856>).
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2025-03-25 |
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r-rstan
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public |
User-facing R functions are provided to parse, compile, test, estimate, and analyze Stan models by accessing the header-only Stan library provided by the 'StanHeaders' package. The Stan project develops a probabilistic programming language that implements full Bayesian statistical inference via Markov Chain Monte Carlo, rough Bayesian inference via 'variational' approximation, and (optionally penalized) maximum likelihood estimation via optimization. In all three cases, automatic differentiation is used to quickly and accurately evaluate gradients without burdening the user with the need to derive the partial derivatives.
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2025-03-25 |
