Trending packages

ggrastr — 1.0.2

Rasterize Layers for 'ggplot2'

pcreg — 0.1.1

Advanced Methods for Principal Component Analysis and Principal Component Regression

moocore — 0.3.1

Core Mathematical Functions for Multi-Objective Optimization

micsr — 0.1-5

Microeconometrics with R

webutils — 1.2.2

Utility Functions for Developing Web Applications

plumber — 1.3.3

An API Generator for R

sodium — 1.4.0

A Modern and Easy-to-Use Crypto Library

scrutiny — 0.6.1

Error Detection in Science

NNS — 13.0

Nonlinear Nonparametric Statistics

NADA — 1.6-1.2

Nondetects and Data Analysis for Environmental Data

linreg — 0.1.0

Linear Regression and Model Selection Framework

arg — 0.1.1

Clean and Simple Argument Checking

aisdk — 1.4.12

Unified Interface for AI Model Providers

fru — 0.0.7

A Blazing Fast Implementation of Random Forest

argparser — 0.7.3

Command-Line Argument Parser

autoann — 0.1.0

Neural Network–Based Model Selection and Forecasting

enrichit — 0.2.0

'C++' Implementations of Functional Enrichment Analysis

duckspatial — 1.2.0

R Interface to 'DuckDB' Database with Spatial Extension

terra — 1.9-34

Spatial Data Analysis

ars — 0.8

Adaptive Rejection Sampling

disposables — 1.0.3

Create Disposable R Packages for Testing

corrr — 0.4.5

Correlations in R

SkewHyperbolic — 0.4-2

The Skew Hyperbolic Student t-Distribution

crs — 0.15-45

Categorical Regression Splines

suntools — 1.1.0

Calculate Sun Position, Sunrise, Sunset, Solar Noon and Twilight

geoarrow — 0.4.3

Extension Types for Spatial Data for Use with 'Arrow'

rbenchmark — 1.0.1

Benchmarking Routine for R

GeneralizedHyperbolic — 0.8-7

The Generalized Hyperbolic Distribution

mixopt — 0.1.3

Mixed Variable Optimization

splitfngr — 0.1.2

Combined Evaluation and Split Access of Functions

scam — 1.2-22

Shape Constrained Additive Models

GauPro — 0.2.17

Gaussian Process Fitting

pkgKitten — 0.2.4

Create Simple Packages Which Do not Upset R Package Checks

statsExpressions — 2.0.0

Tidy Dataframes and Expressions with Statistical Details

hrbrthemes — 0.9.3

Additional Themes, Theme Components and Utilities for 'ggplot2'

ggstatsplot — 1.0.0

'ggplot2' Based Plots with Statistical Details

aricode — 1.1.0

Efficient Computations of Standard Clustering Comparison Measures

limSolve — 2.0.3

Solving Linear Inverse Models

pcalg — 2.7-12

Methods for Graphical Models and Causal Inference

hierfstat — 0.5-11

Estimation and Tests of Hierarchical F-Statistics

bsts — 0.9.11

Bayesian Structural Time Series

otel — 0.2.0

OpenTelemetry R API

threejs — 0.3.4

Interactive 3D Scatter Plots, Networks and Globes

aplot — 0.3.0

Decorate a 'ggplot' with Associated Information

makedummies — 1.2.1

Create Dummy Variables from Categorical Data

shinystan — 2.7.0

Interactive Visual and Numerical Diagnostics and Posterior Analysis for Bayesian Models

conquer — 1.3.3

Convolution-Type Smoothed Quantile Regression

leidenAlg — 1.1.8

Implements the Leiden Algorithm via an R Interface

metabook — 0.2-0

Data Sets and Code for "Meta-Analysis with R"

shinythemes — 1.2.0

Themes for Shiny

colourpicker — 1.3.0

A Colour Picker Tool for Shiny and for Selecting Colours in Plots

sccore — 1.0.7

Core Utilities for Single-Cell RNA-Seq

hdi — 0.1-10

High-Dimensional Inference

dygraphs — 1.1.1.6

Interface to 'Dygraphs' Interactive Time Series Charting Library

gaston — 1.6

Genetic Data Handling (QC, GRM, LD, PCA) & Linear Mixed Models

eulerr — 8.1.0

Area-Proportional Euler and Venn Diagrams

bspm — 0.5.8

Bridge to System Package Manager

scales — 1.4.0

Scale Functions for Visualization

jmvcore — 2.7.35

Dependencies for the 'jamovi' Framework

bayesplot — 1.15.0

Plotting for Bayesian Models

brand.yml — 0.1.0

Unified Branding with a Simple YAML File

log4r — 0.4.4

A Fast and Lightweight Logging System for R, Based on 'log4j'

infotheo — 1.2.0.1

Information-Theoretic Measures

Boom — 0.9.16

Bayesian Object Oriented Modeling

tmvnsim — 1.0-2

Truncated Multivariate Normal Simulation

expsmooth — 2.3

Data Sets from "Forecasting with Exponential Smoothing"

tinytest — 1.4.3

Lightweight and Feature Complete Unit Testing Framework

rstantools — 2.6.0

Tools for Developing R Packages Interfacing with 'Stan'

rstanarm — 2.32.2

Bayesian Applied Regression Modeling via Stan

dartR — 2.9.9.5

Importing and Analysing 'SNP' and 'Silicodart' Data Generated by Genome-Wide Restriction Fragment Analysis

class — 7.3-23

Functions for Classification

shinyjs — 2.1.1

Easily Improve the User Experience of Your Shiny Apps in Seconds

ggm — 2.5.2

Graphical Markov Models with Mixed Graphs

partykit — 1.2-27

A Toolkit for Recursive Partytioning

spatstat — 3.6-1

Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests

mapview — 2.11.4

Interactive Viewing of Spatial Data in R

irlba — 2.3.7

Fast Truncated Singular Value Decomposition and Principal Components Analysis for Large Dense and Sparse Matrices

jinjar — 0.3.2

Template Engine Inspired by 'Jinja'

shinytest2 — 0.5.1

Testing for Shiny Applications

lme4 — 2.0-1

Linear Mixed-Effects Models using 'Eigen' and S4

pkgcache — 2.2.5

Cache 'CRAN'-Like Metadata and R Packages

pegas — 1.4

Population and Evolutionary Genetics Analysis System

segmented — 2.2-1

Regression Models with Break-Points / Change-Points Estimation (with Possibly Random Effects)

yyjsonr — 0.1.22

Fast 'JSON', 'NDJSON' and 'GeoJSON' Parser and Generator

ggridges — 0.5.7

Ridgeline Plots in 'ggplot2'

marquee — 1.2.1

Markdown Parser and Renderer for R Graphics

babynames — 1.0.1

US Baby Names 1880-2017

StanHeaders — 2.32.10

C++ Header Files for Stan

lbfgs — 1.2.1.2

Limited-memory BFGS Optimization

AICcmodavg — 2.3-4

Model Selection and Multimodel Inference Based on (Q)AIC(c)

ggplot2 — 4.0.3

Create Elegant Data Visualisations Using the Grammar of Graphics

opdisDownsampling — 1.6

Optimal Distribution Preserving Down-Sampling of Bio-Medical Data

gson — 0.2.0

Base Class and Methods for 'gson' Format

rstan — 2.32.7

R Interface to Stan

mcmcse — 1.5-1

Monte Carlo Standard Errors for MCMC

bnlearn — 5.1

Bayesian Network Structure Learning, Parameter Learning and Inference

repurrrsive — 1.1.0

Examples of Recursive Lists and Nested or Split Data Frames

RUnit — 0.4.33.1

R Unit Test Framework

unmarked — 1.5.1

Models for Data from Unmarked Animals

duckdb — 1.5.4.2

DBI Package for the DuckDB Database Management System