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This package provides an R client for jq, a JSON processor. jq allows the following with JSON data: index into, parse, do calculations, cut up and filter, change key names and values, perform conditionals and comparisons, and more.
This package provides conditional inference procedures for the general independence problem including two-sample, K-sample (non-parametric ANOVA), correlation, censored, ordered and multivariate problems.
This package provides smooth additive quantile regression models, fitted using the methods of Fasiolo et al. (2017). Differently from quantreg, the smoothing parameters are estimated automatically by marginal loss minimization, while the regression coefficients are estimated using either PIRLS or Newton algorithm. The learning rate is determined so that the Bayesian credible intervals of the estimated effects have approximately the correct coverage. The main function is qgam() which is similar to gam() in the mgcv package, but fits non-parametric quantile regression models.
This package provides functions for performing phylogenetic comparative analyses.
This package implements two methods for performing a constrained principal component analysis (PCA), where non-negativity and/or sparsity constraints are enforced on the principal axes (PAs). The function nsprcomp computes one principal component (PC) after the other. Each PA is optimized such that the corresponding PC has maximum additional variance not explained by the previous components. In contrast, the function nscumcomp jointly computes all PCs such that the cumulative variance is maximal. Both functions have the same interface as the prcomp function from the stats package (plus some extra parameters).
This package lets you easily use Bootstrap icons inside Shiny apps and R Markdown documents. More generally, icons can be inserted in any htmltools document through inline SVG.
This package provides implementations of the SHA-3 cryptographic hash and SHAKE256 extendable-output functions (XOF).
This package provides tools for accessing the Botanical Information and Ecology Network (BIEN) database. The BIEN database contains cleaned and standardized botanical data including occurrence, trait, plot and taxonomic data. This package provides functions that query the BIEN database by constructing and executing optimized SQL queries.
This package computes moments of univariate truncated T distribution. There is only one exported function, e_trunct, which should be seen for details.
This package provides functions for reading, writing, plotting, and manipulating phylogenetic trees, analyses of comparative data in a phylogenetic framework, ancestral character analyses, analyses of diversification and macroevolution, computing distances from DNA sequences, and several other tools.
This package provides the URL checking tools available in R 4.1+ as a package for earlier versions of R. It also uses concurrent requests so can be much faster than the serial versions.
This package provides tools for maximum a posteriori estimation for linear and generalized linear mixed-effects models in a Bayesian setting. It extends the lme4 package.
This package provides an R API to the Open Source Geometry Engine (GEOS) library and a vector format with which to efficiently store GEOS geometries. High-performance functions to extract information from, calculate relationships between, and transform geometries are provided. Finally, facilities to import and export geometry vectors to other spatial formats are provided.
This package provides infrastructure for psychometric modeling such as data classes (for item response data and paired comparisons), basic model fitting functions (for Bradley-Terry, Rasch, parametric logistic IRT, generalized partial credit, rating scale, multinomial processing tree models), extractor functions for different types of parameters (item, person, threshold, discrimination, guessing, upper asymptotes), unified inference and visualizations, and various datasets for illustration. It is intended as a common lightweight and efficient toolbox for psychometric modeling and a common building block for fitting psychometric mixture models in package psychomix and trees based on psychometric models in package psychotree.
This package provides a set of functions with example data for graphing, pruning, and mapping models. These models are from hierarchical clustering, and classification and regression trees.
mlr3pipelines enriches mlr3 with a diverse set of pipelining operators (PipeOps) that can be composed into graphs. Operations exist for data preprocessing, model fitting, and ensemble learning. Graphs can themselves be treated as mlr3 Learners and can therefore be resampled, benchmarked, and tuned.
This package provides support for iterators, which allow a programmer to traverse through all the elements of a vector, list, or other collection of data.
This package provides a suite of tools designed to build attractive command line interfaces (CLIs). It includes tools for drawing rules, boxes, trees, and Unicode symbols with ASCII alternatives.
This package provides C-based tools for converting large scatterplot data to rasters. It speeds up plotting of data with millions of points.
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 with out 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.
This package provides a parallel backend for the %dopar% function using the snow package.
This package provides a low-level interface to the Java VM very much like .C/.Call and friends. It allows the creation of objects, calling methods and accessing fields.
This package lets you rarefy data, calculate diversity and plot the results.
This package provides various R programming tools for data manipulation, including:
medical unit conversions
combining objects
character vector operations
factor manipulation
obtaining information about R objects
generating fixed-width format files
extricating components of date and time objects
operations on columns of data frames
matrix operations
operations on vectors and data frames
value of last evaluated expression
wrapper for
samplethat ensures consistent behavior for both scalar and vector arguments