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This package provides tools for the estimation of indicators on social exclusion and poverty, as well as an implementation of Pareto tail modeling for empirical income distributions.
This package provides multiple pairwise tests.
Functions to help implement the extraction / subsetting / indexing function [ and replacement function [<- of custom matrix-like types (based on S3, S4, etc.), modeled as closely to the base matrix class as possible (with tests to prove it).
The DHARMa package uses a simulation-based approach to create readily interpretable scaled (quantile) residuals for fitted (generalized) linear mixed models. 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, phylogenetic and temporal autocorrelation.
Finding an optimal Bayesian experimental design involves maximizing an objective function given by the expectation of some appropriately chosen utility function with respect to the joint distribution of unknown quantities (including responses). This objective function is usually not available in closed form and the design space can be continuous and of high dimensionality. This package uses Approximate Coordinate Exchange (ACE) to maximise an approximation to the expectation of the utility function.
This package provides tools to process and print UTF-8 encoded international text (Unicode). Input, validate, normalize, encode, format, and display.
The feature package contains functions to display and compute kernel density estimates, significant gradient and significant curvature regions. Significant gradient and/or curvature regions often correspond to significant features (e.g. local modes).
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.
This package aims to streamline and accelerate the process of saving and loading R objects, improving speed and compression compared to other methods. The package provides two compression formats: the qs2 format, which uses R serialization via the C API while optimizing compression and disk I/O, and the qdata format, featuring custom serialization for slightly faster performance and better compression. Additionally, the qs2 format can be directly converted to the standard RDS format, ensuring long-term compatibility with future versions of R.
Statistical and biological validation of clustering results. This package implements Dunn Index, Silhouette, Connectivity, Stability, BHI and BSI. Further information can be found in Brock, G et al. (2008) <doi: 10.18637/jss.v025.i04>.
This package provides utilities to understand and describe posterior distributions and Bayesian models. It includes point-estimates such as Maximum A Posteriori (MAP), measures of dispersion such as Highest Density Interval (HDI), and indices used for null-hypothesis testing (such as ROPE percentage and pd).
Reshape2 is an R library to flexibly restructure and aggregate data using just two functions: melt and dcast (or acast).
An R interface to the Pushbullet messaging service which provides fast and efficient notifications (and file transfer) between computers, phones and tablets.
This package includes functions for processing GeoJson objects relying on RFC 7946. The geojson encoding is based on json11, a tiny JSON library for C++11. Furthermore, the source code is exported in R through the Rcpp and RcppArmadillo packages.
The Rsolnp package implements a general non-linear augmented Lagrange multiplier method solver, a sequential quadratic programming (SQP) based solver).
This package provides tools for clustering and principal component analysis (with robust methods, and parallelized functions).
Colored terminal output on terminals that support ANSI color and highlight codes. It also works in Emacs ESS. ANSI color support is automatically detected. Colors and highlighting can be combined and nested. New styles can also be created easily. This package was inspired by the "chalk" JavaScript project.
The extrafont package makes it easier to use fonts other than the basic PostScript fonts that R uses. Fonts that are imported into extrafont can be used with PDF or PostScript output files. There are two hurdles for using fonts in PDF (or Postscript) output files:
Making R aware of the font and the dimensions of the characters.
Embedding the fonts in the PDF file so that the PDF can be displayed properly on a device that doesn't have the font. This is usually needed if you want to print the PDF file or share it with others.
The extrafont package makes both of these things easier.
This package provides a convenience wrapper that uses the rmarkdown package to render small snippets of code to target formats that include both code and output. The goal is to encourage the sharing of small, reproducible, and runnable examples on code-oriented websites or email. reprex also extracts clean, runnable R code from various common formats, such as copy/paste from an R session.
This package offers methods to perform asymptotically bias-corrected regularized linear discriminant analysis (ABC_RLDA) for cost-sensitive binary classification. The bias-correction is an estimate of the bias term added to regularized discriminant analysis that minimizes the overall risk.
R comes with a suite of utilities for linear algebra with "numeric" (double precision) vectors/matrices. However, sometimes single precision (or less!) is more than enough for a particular task. This package extends R's linear algebra facilities to include 32-bit float (single precision) data. Float vectors/matrices have half the precision of their "numeric"-type counterparts but are generally faster to numerically operate on, for a performance vs accuracy trade-off.
This package provides an interface to Amazon Web Services, including storage, database, and compute services, such as Simple Storage Service (S3), DynamoDB NoSQL database, and Lambda functions-as-a-service.
This package provides a set of predicates and assertions for checking the properties of models. This is mainly for use by other package developers who want to include run-time testing features in their own packages.
This package provides a collection of functions to help in the analysis of right-censored survival data. These extend the methods available in the survival package.