R-tgb provides Bayesian nonstationary regression and treed Gaussian processes. In addition, it provides visualization functions, tree drawing, sensitivity analysis, multi-resolution models, and sequential experimental design tools, including ALM, ALC, and expected improvement for optimizing noisy black-box functions.

This started out as a package for file and string manipulation. Since then, the fs and strex packages emerged, offering functionality previously given by this package. Those packages have hence almost pushed filesstrings into extinction. However, it still has a small number of unique, handy file manipulation functions which can be seen in the vignette. One example is a function to remove spaces from all file names in a directory.

The Tweedie compound Poisson distribution is a mixture of a degenerate distribution at the origin and a continuous distribution on the positive real line. It has been applied in a wide range of fields in which continuous data with exact zeros regularly arise. The cplm package provides likelihood based and Bayesian procedures for fitting common Tweedie compound Poisson linear models. In particular, models with hierarchical structures or extra zero inflation can be handled. Further, the package implements the Gini index based on an ordered version of the Lorenz curve as a robust model comparison tool involving zero-inflated and highly skewed distributions.

This package provides a comprehensive collection for structural multivariate function estimation using smoothing splines.

This package provides a set of predicates and assertions for checking the properties of (country independent) complex data types. This is mainly for use by other package developers who want to include run-time testing features in their own packages.

This package provides well-known outlier detection techniques in the univariate case. Methods to deal with skewed distribution are included too. The Hidiroglou-Berthelot (1986) method to search for outliers in ratios of historical data is implemented as well. When available, survey weights can be used in outliers detection.

This package provides tools to obtain estimated marginal means (EMMs) for many linear, generalized linear, and mixed models. It can be used to compute contrasts or linear functions of EMMs, trends, and comparisons of slopes.

Extracts plain text from Rich Text Format (RTF) file.

This package provides basic functions, implemented in C, for large data manipulation. Fast vectorised ifelse()/nested if()/switch() functions, psum()/pprod() functions equivalent to pmin()/pmax() plus others which are missing from base R. Most of these functions are callable at C level.

This package provides methods and algorithms for discrete optimization, e.g. knapsack and subset sum procedures, derivative-free Nelder-Mead and Hooke-Jeeves minimization, and some (evolutionary) global optimization functions.

This package provides an implementation of dimensionality reduction via regression using Kernel Ridge Regression.

This package adds additional Twitter Bootstrap components to Shiny.

This package provides a simple router for your Shiny apps. The router allows you to create dynamic web applications with a real-time User Interface and easily share url to pages within your Shiny apps.

Allow numbers to be presented in an English language version, one, two, three, ... Ordinals are also available, first, second, third, ... and indefinite article choice, "a" or "an".

This package implements affinity propagation clustering introduced by Frey and Dueck (2007). The package further provides leveraged affinity propagation and an algorithm for exemplar-based agglomerative clustering that can also be used to join clusters obtained from affinity propagation. Various plotting functions are available for analyzing clustering results.

Create interactive ggplot2 graphics using htmlwidgets.

This package provides a wrapper around the C++ library polylabel from Mapbox, providing an efficient routine for finding the approximate pole of inaccessibility of a polygon, which usually serves as an excellent candidate for labeling of a polygon.

This is yet another command-line argument parser which wraps the powerful Perl module Getopt::Long and with some adaptation for easier use in R. It also provides a simple way for variable interpolation in R.

This is a package for developers to check user-supplied function arguments. It is designed to be simple, fast and customizable. Error messages follow the tidyverse style guide.

The R kernel for the Jupyter environment executes R code which the front-end (Jupyter Notebook or other front-ends) submits to the kernel via the network.

This package implements fast hierarchical, agglomerative clustering routines. Part of the functionality is designed as drop-in replacement for existing routines: linkage() in the SciPy package scipy.cluster.hierarchy, hclust() in R's stats package, and the flashClust package. It provides the same functionality with the benefit of a much faster implementation. Moreover, there are memory-saving routines for clustering of vector data, which go beyond what the existing packages provide.

This package contains data structures and algorithms for sparse arrays and matrices, based on index arrays and simple triplet representations, respectively.

This package lets you plot model surfaces for a wide variety of models using partial dependence plots and other techniques. Also plot model residuals and other information on the model.

Set of tools for reading and processing spatial data. The aim is to supply the workflow to create thematic maps. This package also facilitates tmap, the package for visualizing thematic maps.