This package provides functions for estimating Rasch model parameters using the Generalized Linear Model (GLM) framework. The methods implemented are based on Brown (2018, ISBN:978-3-319-93547-8) <doi:10.1007/978-3-319-93549-2> and Debelak et al. (2022, ISBN:978-1-138-71046-7) <doi:10.1201/9781315200620>.

Generates concise alternative text for data visualizations created with ggplot2'. Descriptions are produced by inspecting plot layers, labels, scales, and facets, with support for multiple languages and alternative text stored in plot metadata.

Modified versions of the lag() and summary() functions: glag() and gsummary(). The prefix g is a reminder of who to blame if things do not work as they should.

Simulating single cell RNA-seq data with complicated structure. This package is developed based on the Splat method (Zappia, Phipson and Oshlack (2017) <doi:10.1186/s13059-017-1305-0>). GeneScape incorporates additional features to simulate single cell RNA-seq data with complicated differential expression and correlation structures, such as sub-cell-types, correlated genes (pathway genes) and hub genes.

This package creates bar plots with rounded corners using ggplot2'. The code in this package was adapted from a solution provided by Stack Overflow user sthoch in the following post <https://stackoverflow.com/questions/62176038/r-ggplot2-bar-chart-with-round-corners-on-top-of-bar>.

This package provides one-liner functions for common legend and guide operations in ggplot2'. Simplifies legend positioning, styling, wrapping, and collection across multi-panel plots created with patchwork or cowplot'.

Estimates the Gini index and computes variances and confidence intervals for finite and infinite populations, using different methods; also computes Gini index for continuous probability distributions, draws samples from continuous probability distributions with Gini indices set by the user; uses Rcpp'. References: Muñoz et al. (2023) <doi:10.1177/00491241231176847>. à lvarez et al. (2021) <doi:10.3390/math9243252>. Giorgi and Gigliarano (2017) <doi:10.1111/joes.12185>. Langel and Tillé (2013) <doi:10.1111/j.1467-985X.2012.01048.x>.

Add vector field layers to ggplots. Ideal for visualising wind speeds, water currents, electric/magnetic fields, etc. Accepts data.frames, simple features (sf), and spatiotemporal arrays (stars) objects as input. Vector fields are depicted as arrows starting at specified locations, and with specified angles and radii.

Estimation of generalized linear models with correlated/clustered observations by use of generalized estimating equations (GEE). See e.g. Halekoh and Højsgaard, (2005, <doi:10.18637/jss.v015.i02>), for details. Several types of clustering are supported, including exchangeable variance structures, AR1 structures, M-dependent, user-specified variance structures and more. The model fitting computations are performed using modified code from the geeM package, while the interface and output objects have been written to resemble the geepack package. The package also contains additional tools for working with and inspecting results from the geepack package, e.g. a confint method for geeglm objects from geepack'.

Splits date and time of day components from continuous datetime objects, then plots them using grammar of graphics ('ggplot2'). Plots can also be decorated with solar cycle information (e.g., sunset, sunrise, etc.). This is useful for visualising data that are associated with the solar cycle.

Visualise the results of F test to compare two variances, Student's t-test, test of equal or given proportions, Pearson's chi-squared test for count data and test for association/correlation between paired samples.

Additional annotations, stats, geoms and scales for plotting "light" spectra with ggplot2', together with specializations of ggplot() and autoplot() methods for spectral data and waveband definitions stored in objects of classes defined in package photobiology'. Part of the r4photobiology suite, Aphalo P. J. (2015) <doi:10.19232/uv4pb.2015.1.14>.

Create engaging population and point plots charts in R. ggpop allows users to represent population data and points proportionally using customizable icons, facilitating the creation of circular representative population charts as well as any point-plots.

This package provides functions which make using the Generalized Regression Estimator(GREG) J.N.K. Rao, Isabel Molina, (2015) <doi:10.3390/f11020244> and the Generalized Regression Estimator Operating on Resolutions of Y (GREGORY) easier. The functions are designed to work well within a forestry context, and estimate multiple estimation units at once. Compared to other survey estimation packages, this function has greater flexibility when describing the linear model.

The function combines a scatter plot with ridgelines to better visualise the distribution between sample groups. The plot is created with ggplot2'.

Enables users to create simple plots of biological culture plates as well as microplates. Both continuous and discrete values can be plotted onto the plate layout.

Estimates within and between time point interactions in experience sampling data, using the Graphical vector autoregression model in combination with regularization. See also Epskamp, Waldorp, Mottus & Borsboom (2018) <doi:10.1080/00273171.2018.1454823>.

Unconstrained and constrained maximum likelihood estimation of structural and reduced form Gaussian mixture vector autoregressive, Student's t mixture vector autoregressive, and Gaussian and Student's t mixture vector autoregressive models, quantile residual tests, graphical diagnostics, simulations, forecasting, and estimation of generalized impulse response function and generalized forecast error variance decomposition. Leena Kalliovirta, Mika Meitz, Pentti Saikkonen (2016) <doi:10.1016/j.jeconom.2016.02.012>, Savi Virolainen (2025) <doi:10.1080/07350015.2024.2322090>, Savi Virolainen (in press) <doi:10.1016/j.ecosta.2025.09.003>.

Access data provided by the United States Government Publishing Office (GPO) GovInfo API (<https://github.com/usgpo/api>).

This package implements the G-Formula method for causal inference with time-varying treatments and confounders using Bayesian multiple imputation methods, as described by Bartlett et al (2025) <doi:10.1177/09622802251316971>. It creates multiple synthetic imputed datasets under treatment regimes of interest using the mice package. These can then be analysed using rules developed for analysing multiple synthetic datasets.

Multidimensional systems allow complex queries to be carried out in an easy way. The geographical dimension, together with the temporal dimension, plays a fundamental role in multidimensional systems. Through this package, vector geographic data layers can be associated to the attributes of geographic dimensions, so that the results of multidimensional queries can be obtained directly as vector layers. The multidimensional structures on which we can define the queries can be created from a flat table or imported directly using functions from this package.

Simplifies the creation, management, and updating of local databases using data extracted from Google Earth Engine ('GEE'). It integrates with GEE to store, aggregate, and process spatio-temporal data, leveraging SQLite for efficient, serverless storage. The geeLite package provides utilities for data transformation and supports real-time monitoring and analysis of geospatial features, making it suitable for researchers and practitioners in geospatial science. For details, see Kurbucz and Andrée (2025) "Building and Managing Local Databases from Google Earth Engine with the geeLite R Package" <https://hdl.handle.net/10986/43165>.

This package provides a framework for creating plots with glowing points.

Create stunning network experiences powered by the G6 graph visualisation engine JavaScript library <https://g6.antv.antgroup.com/en>. In shiny mode, modify your graph directly from the server function to dynamically interact with nodes and edges. Select your favorite layout among 20 choices. 15 behaviors are available such as interactive edge creation, collapse-expand and brush select. 17 plugins designed to improve the user experience such as a mini-map, toolbars and grid lines. Customise the look and feel of your graph with comprehensive options for nodes, edges and more.