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

Found 119 packages in 0.02 seconds

gnm — by Heather Turner, 3 years 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.

MatrixModels — by Martin Maechler, a year ago

Modelling with Sparse and Dense Matrices

Generalized Linear Modelling with sparse and dense 'Matrix' matrices, using modular prediction and response module classes.

rstanarm — by Ben Goodrich, a year 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.

Microsoft365R — by Hong Ooi, 2 years ago

Interface to the 'Microsoft 365' Suite of Cloud Services

An interface to the 'Microsoft 365' (formerly known as 'Office 365') suite of cloud services, building on the framework supplied by the 'AzureGraph' package. Enables access from R to data stored in 'Teams', 'SharePoint Online' and 'OneDrive', including the ability to list drive folder contents, upload and download files, send messages, and retrieve data lists. Also provides a full-featured 'Outlook' email client, with the ability to send emails and manage emails and mail folders.

radarchart — by Doug Ashton, 10 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.

GLMMadaptive — by Dimitris Rizopoulos, 2 years ago

Generalized Linear Mixed Models using Adaptive Gaussian Quadrature

Fits generalized linear mixed models for a single grouping factor under maximum likelihood approximating the integrals over the random effects with an adaptive Gaussian quadrature rule; Jose C. Pinheiro and Douglas M. Bates (1995) .

POMS — by Gavin Douglas, 4 years 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) .

FuncDiv — by Gavin Douglas, 4 years ago

Compute Contributional Diversity Metrics

Compute alpha and beta contributional diversity metrics, which is intended for linking taxonomic and functional microbiome data. See 'GitHub' repository for the tutorial: < https://github.com/gavinmdouglas/FuncDiv/wiki>. Citation: Gavin M. Douglas, Sunu Kim, Morgan G. I. Langille, B. Jesse Shapiro (2023) .

expm — by Martin Maechler, 25 days ago

Matrix Exponential, Log, 'etc'

Computation of the matrix exponential, logarithm, sqrt, and related quantities, using traditional and modern methods.

PerformanceAnalytics — by Brian G. Peterson, 5 months 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.