Preliminary Visualisation of Data

Create preliminary exploratory data visualisations of an entire dataset to identify problems or unexpected features using 'ggplot2'.

Analysis and Visualization of Complex Networks

Provides tools for the analysis, visualization, and manipulation of dynamical, social (Saqr et al. (2024) ) and complex networks (Saqr et al. (2025) ). The package supports multiple network formats and offers flexible tools for heterogeneous, multi-layer, and hierarchical network analysis with simple syntax and extensive toolset.

Interactive Visualizations for Profiling R Code

Interactive visualizations for profiling R code.

Visualizing and Analyzing Animal Track Data

Contains functions to access movement data stored in 'movebank.org' as well as tools to visualize and statistically analyze animal movement data, among others functions to calculate dynamic Brownian Bridge Movement Models. Move helps addressing movement ecology questions.

Interactive Statistical Data Visualization

An extendable toolkit for interactive data visualization and exploration.

Data Visualization for Statistics in Social Science

Collection of plotting and table output functions for data visualization. Results of various statistical analyses (that are commonly used in social sciences) can be visualized using this package, including simple and cross tabulated frequencies, histograms, box plots, (generalized) linear models, mixed effects models, principal component analysis and correlation matrices, cluster analyses, scatter plots, stacked scales, effects plots of regression models (including interaction terms) and much more. This package supports labelled data.

Visualization and Analysis Tools for Neural Networks

Visualization and analysis tools to aid in the interpretation of neural network models. Functions are available for plotting, quantifying variable importance, conducting a sensitivity analysis, and obtaining a simple list of model weights.

Visualizing Hypothesis Tests in Multivariate Linear Models

Provides HE plot and other functions for visualizing hypothesis tests in multivariate linear models. HE plots represent sums-of-squares-and-products matrices for linear hypotheses and for error using ellipses (in two dimensions) and ellipsoids (in three dimensions). It also provides other tools for analysis and graphical display of the models such as robust methods and homogeneity of variance covariance matrices. The related 'candisc' package provides visualizations in a reduced-rank canonical discriminant space when there are more than a few response variables.

S3 Infrastructure for Regular and Irregular Time Series (Z's Ordered Observations)

An S3 class with methods for working with regular and irregular time series. The class stores data as numeric vectors/matrices (or factors) along with a time index of arbitrary class (including numeric, Date, POSIXct, chron, yearmon, yearqtr, etc.). Functions and methods are consistent with the ts class and base R and also extend standard generics. Tools include: Data import/export, coercion, visualization (with base R, 'ggplot2', 'lattice', 'tinyplot'), alignment and merging, aggregation, lags and subsets, rolling analytics, and time-based interpolation/filling. The design is introduced in Zeileis and Grothendieck (2005) .

Interactive Visual and Numerical Diagnostics and Posterior Analysis for Bayesian Models

A graphical user interface for interactive Markov chain Monte Carlo (MCMC) diagnostics and plots and tables helpful for analyzing a posterior sample. The interface is powered by the 'Shiny' web application framework from 'RStudio' and works with the output of MCMC programs written in any programming language (and has extended functionality for 'Stan' models fit using the 'rstan' and 'rstanarm' packages).