Examples: visualization, C++, networks, data cleaning, html widgets, ropensci.

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permute — by Gavin L. Simpson, 2 years ago

Functions for Generating Restricted Permutations of Data

A set of restricted permutation designs for freely exchangeable, line transects (time series), and spatial grid designs plus permutation of blocks (groups of samples) is provided. 'permute' also allows split-plot designs, in which the whole-plots or split-plots or both can be freely-exchangeable or one of the restricted designs. The 'permute' package is modelled after the permutation schemes of 'Canoco 3.1' (and later) by Cajo ter Braak.

lme4 — by Ben Bolker, 21 days ago

Linear Mixed-Effects Models using 'Eigen' and S4

Fit linear and generalized linear mixed-effects models. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the 'Eigen' C++ library for numerical linear algebra and 'RcppEigen' "glue".

minqa — by Katharine M. Mullen, 7 months ago

Derivative-Free Optimization Algorithms by Quadratic Approximation

Derivative-free optimization by quadratic approximation based on an interface to Fortran implementations by M. J. D. Powell.

gnm — by Heather Turner, 7 months ago

Generalized Nonlinear Models

Functions to specify and fit generalized nonlinear models, including models with multiplicative interaction terms such as the UNIDIFF model from sociology and the AMMI model from crop science, and many others. Over-parameterized representations of models are used throughout; functions are provided for inference on estimable parameter combinations, as well as standard methods for diagnostics etc.

jsonvalidate — by Rich FitzJohn, 2 years ago

Validate 'JSON' Schema

Uses the node library 'is-my-json-valid' or 'ajv' to validate 'JSON' against a 'JSON' schema. Drafts 04, 06 and 07 of 'JSON' schema are supported.

fastglm — by Jared Huling, 2 years ago

Fast and Stable Fitting of Generalized Linear Models using 'RcppEigen'

Fits generalized linear models efficiently using 'RcppEigen'. The iteratively reweighted least squares implementation utilizes the step-halving approach of Marschner (2011) to help safeguard against convergence issues.

rstanarm — by Ben Goodrich, 3 months ago

Bayesian Applied Regression Modeling via Stan

Estimates previously compiled regression models using the 'rstan' package, which provides the R interface to the Stan C++ library for Bayesian estimation. Users specify models via the customary R syntax with a formula and data.frame plus some additional arguments for priors.

radarchart — by Doug Ashton, 7 years ago

Radar Chart from 'Chart.js'

Create interactive radar charts using the 'Chart.js' 'JavaScript' library and the 'htmlwidgets' package. 'Chart.js' < http://www.chartjs.org/> is a lightweight library that supports several types of simple chart using the 'HTML5' canvas element. This package provides an R interface specifically to the radar chart, sometimes called a spider chart, for visualising multivariate data.

POMS — by Gavin Douglas, a year ago

Phylogenetic Organization of Metagenomic Signals

Code to identify functional enrichments across diverse taxa in phylogenetic tree, particularly where these taxa differ in abundance across samples in a non-random pattern. The motivation for this approach is to identify microbial functions encoded by diverse taxa that are at higher abundance in certain samples compared to others, which could indicate that such functions are broadly adaptive under certain conditions. See 'GitHub' repository for tutorial and examples: < https://github.com/gavinmdouglas/POMS/wiki>. Citation: Gavin M. Douglas, Molly G. Hayes, Morgan G. I. Langille, Elhanan Borenstein (2022) .

PerformanceAnalytics — by Brian G. Peterson, 4 years ago

Econometric Tools for Performance and Risk Analysis

Collection of econometric functions for performance and risk analysis. In addition to standard risk and performance metrics, this package aims to aid practitioners and researchers in utilizing the latest research in analysis of non-normal return streams. In general, it is most tested on return (rather than price) data on a regular scale, but most functions will work with irregular return data as well, and increasing numbers of functions will work with P&L or price data where possible.