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JDistlib is the Java Statistical Distribution Library, a Java package that provides routines for various statistical distributions.
This is a package for Non-Negative Linear Models (NNLM). It implements fast sequential coordinate descent algorithms for non-negative linear regression and non-negative matrix factorization (NMF). It supports mean square error and Kullback-Leibler divergence loss. Many other features are also implemented, including missing value imputation, domain knowledge integration, designable W and H matrices and multiple forms of regularizations.
Command-line tool and C library for reading files from popular stats packages like SAS, Stata and SPSS.
Did you ever wish you could make scatter plots with cat shaped points? Now you can!
Visual predictive checks are a commonly used diagnostic plot in pharmacometrics, showing how certain statistics (percentiles) for observed data compare to those same statistics for data simulated from a model. The package can generate VPCs for continuous, categorical, censored, and (repeated) time-to-event data.
George is a fast and flexible Python library for Gaussian Process (GP) Regression, focused on efficiently evaluating the marginalized likelihood of a dataset under a GP prior, even as this dataset gets Big.
This package provides a backend for the selecting functions of the tidyverse. It makes it easy to implement select-like functions in your own packages in a way that is consistent with other tidyverse interfaces for selection.
The trimmed k-means clustering method by Cuesta-Albertos, Gordaliza and Matran (1997). This optimizes the k-means criterion under trimming a portion of the points.
Vega-Altair is a declarative statistical visualization library for Python.
This package is a port of the S+ "Robust Library". It provides methods for robust statistics, notably for robust regression and robust multivariate analysis.
This package provides a collection of datasets used in Vega and Vega-Lite examples.
This package provides methods and classes for object-oriented programming in R with or without references. Large effort has been made on making definition of methods as simple as possible with a minimum of maintenance for package developers.
This package provides an implementation of robust location and scatter estimation and robust multivariate analysis with high breakdown point.
This package provides a number of polymodes for working with mixed R files, including Rmarkdown files.
JAGS is Just Another Gibbs Sampler. It is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS. JAGS was written with three aims in mind:
To have a cross-platform engine for the BUGS language;
To be extensible, allowing users to write their own functions, distributions and samplers;
To be a platform for experimentation with ideas in Bayesian modelling.
The RSP markup language provides a powerful markup for controlling the content and output of LaTeX, HTML, Markdown, AsciiDoc, Sweave and knitr documents (and more), e.g. Today's date is <%=Sys.Date()%>. Contrary to many other literate programming languages, with RSP it is straightforward to loop over mixtures of code and text sections, e.g. in month-by-month summaries. RSP has also several preprocessing directives for incorporating static and dynamic contents of external files (local or online) among other things. RSP is ideal for self-contained scientific reports and R package vignettes.
Rapid, simulation-based exact (restricted) likelihood ratio tests for testing the presence of variance components/nonparametric terms for models fit with nlme::lme(), lme4::lmer(), lmeTest::lmer(), gamm4::gamm4(), mgcv::gamm() and SemiPar::spm().
This package provides a toolbox for working with base types, core R features like the condition system, and core Tidyverse features like tidy evaluation.
This package contains a set of functions for working with Random Number Generators (RNGs). In particular, it defines a generic S4 framework for getting/setting the current RNG, or RNG data that are embedded into objects for reproducibility. Notably, convenient default methods greatly facilitate the way current RNG settings can be changed.
This package implements a Dynamic Nested Sampling for computing Bayesian posteriors and evidences.
stb-sprintf implements fast sprintf, snprintf for C/C++.
stb-image is a small and self-contained library for image loading or decoding from file or memory. A variety of formats are supported.
stb-image-resize2 is a library that supports scaling and translation of images.
stb-image-write is a small library for writing image files to the C stdio interface.