This package provides functions for estimating marginal likelihoods, Bayes factors, posterior model probabilities, and normalizing constants in general, via different versions of bridge sampling.

With this package you can add in-app user authentication to Shiny, allowing you to secure publicly hosted apps and build dynamic user interfaces from user information.

This package provides an implementation of an algorithm for general-purpose unconstrained non-linear optimization. The algorithm is of quasi-Newton type with BFGS updating of the inverse Hessian and soft line search with a trust region type monitoring of the input to the line search algorithm. The interface of ucminf is designed for easy interchange with the package optim.

This package provides a framework to create Bootstrap 3 HTML reports from knitr Rmarkdown.

This package provides an API for efficient .hic file data extraction with programmatic matrix access. It doesn't store the pointer data for all the matrices, only the one queried, and currently it only supports matrices.

Artificial Bee Colony (ABC) is one of the most recently defined algorithms by Dervis Karaboga in 2005, motivated by the intelligent behavior of honey bees. It is as simple as Particle Swarm Optimization (PSO) and Differential Evolution (DE) algorithms, and uses only common control parameters such as colony size and maximum cycle number. The r-abcoptim implements the Artificial bee colony optimization algorithm http://mf.erciyes.edu.tr/abc/pub/tr06_2005.pdf. This version is a work-in-progress and is written in R code.

Customize Bootstrap and Bootswatch themes, like colors, fonts, grid layout, to use in Shiny applications, rmarkdown documents and flexdashboard.

This package provides a smooth mapping of multidimensional points into low-dimensional space defined by a self-organizing map. It is designed to work with FlowSOM and flow-cytometry use-cases.

This package provides an R interface to Google's BigQuery database.

This package provides functions for regulation, decomposition and analysis of space-time series. The pastecs library is a PNEC-Art4 and IFREMER initiative to bring PASSTEC 2000 functionalities to R.

This package provides easy-to-use and versatile functions to output R objects in HTML format.

This package is designed as an integrated package for genetic data analysis of both population and family data. Currently, it contains functions for sample size calculations of both population-based and family-based designs, probability of familial disease aggregation, kinship calculation, statistics in linkage analysis, and association analysis involving genetic markers including haplotype analysis with or without environmental covariates. Over years, the package has been developed in-between many projects hence also in line with the name (gap).

This package contains a collection of functions to deal with nonparametric measurement error problems using deconvolution kernel methods. We focus two measurement error models in the package: (1) an additive measurement error model, where the goal is to estimate the density or distribution function from contaminated data; (2) nonparametric regression model with errors-in-variables. The R functions allow the measurement errors to be either homoscedastic or heteroscedastic. To make the deconvolution estimators computationally more efficient in R, we adapt the "Fast Fourier Transform" (FFT) algorithm for density estimation with error-free data to the deconvolution kernel estimation. Several methods for the selection of the data-driven smoothing parameter are also provided in the package. See details in: Wang, X.F. and Wang, B. (2011). Deconvolution estimation in measurement error models: The R package decon. Journal of Statistical Software, 39(10), 1-24.

This package lets you download Google fonts and generate CSS to use in rmarkdown documents and Shiny applications. Some popular fonts are included and ready to use.

Unlike other tools that dynamically link to the Cairo stack, freetypeharfbuzz is statically linked to specific versions of the FreeType and harfbuzz libraries. This ensures deterministic computation of text box extents for situations where reproducible results are crucial (for instance unit tests of graphics).

The smurf package contains the implementation of the Sparse Multi-type Regularized Feature (SMuRF) modeling algorithm to fit generalized linear models (GLMs) with multiple types of predictors via regularized maximum likelihood. Next to the fitting procedure, following functionality is available:

• Selection of the regularization tuning parameter lambda using three different approaches: in-sample, out-of-sample or using cross-validation.

• S3 methods to handle the fitted object including visualization of the coefficients and a model summary.

This package contains functions for non-parametric survival analysis of exact and interval-censored observations.

This package provides a common interface to allow users to specify a model without having to remember the different argument names across different functions or computational engines (e.g. R, Spark, Stan, etc).

This r-physicalactivity package provides a function wearingMarking for classification of monitored wear and nonwear time intervals in accelerometer data collected to assess physical activity. The package also contains functions for making plots of accelerometer data and obtaining the summary of various information including daily monitor wear time and the mean monitor wear time during valid days. The revised package version 0.2-1 improved the functions regarding speed, robustness and add better support for time zones and daylight saving. In addition, several functions were added:

1. the markDelivery can classify days for ActiGraph delivery by mail;

2. the markPAI can categorize physical activity intensity level based on user-defined cut-points of accelerometer counts.

It also supports importing ActiGraph (AGD) files with readActigraph and queryActigraph functions.

This package provides a data frame to xlsx exporter based on libxlsxwriter.

This package implements a James-Stein-type shrinkage estimator for the covariance matrix, with separate shrinkage for variances and correlations. Furthermore, functions are available for fast singular value decomposition, for computing the pseudoinverse, and for checking the rank and positive definiteness of a matrix.

R-hub uses GitHub Actions to run R CMD check and similar package checks. The rhub package helps you set up R-hub for your R package, and start running checks.

This package provides methods for manipulating regression models and for describing these in a style adapted for medical journals. It contains functions for generating an HTML table with crude and adjusted estimates, plotting hazard ratio, plotting model estimates and confidence intervals using forest plots, extending this to comparing multiple models in a single forest plots. In addition to the descriptive methods, there are functions for the robust covariance matrix provided by the sandwich package, a function for adding non-linearities to a model, and a wrapper around the Epi package's Lexis() functions for time-splitting a dataset when modeling non-proportional hazards in Cox regressions.

This package provides data sets for econometrics, including political science.