An interface to the Gmail RESTful API. Allows access to your Gmail messages, threads, drafts and labels.

This package provides functions and methods for: splitting large raster objects into smaller chunks, transferring images from a binary format into raster layers, transferring raster layers into an RData file, calculating the maximum gap (amount of consecutive missing values) of a numeric vector, and fitting harmonic regression models to periodic time series. The homoscedastic harmonic regression model is based on G. Roerink, M. Menenti and W. Verhoef (2000) <doi:10.1080/014311600209814>.

This package provides tools for efficient processing of large, whole genome genotype data sets in variant call format (VCF). It includes several functions to calculate commonly used population genomic metrics and a method for reference panel free genotype imputation, which is described in the preprint Gurke & Mayer (2024) <doi:10.22541/au.172515591.10119928/v1>.

Performing goodness-of-fit tests for stochastic block models used to fit network data. Among the three variants discussed in Karwa et al. (2023) <doi:10.1093/jrsssb/qkad084>, goodness-of-fit test has been performed for the Erdos-Renyi (ER) and Beta versions.

The increasing popularity of geographically weighted (GW) techniques has resulted in the development of several R packages, such as GWmodel'. To facilitate their usages, GWmodelVis provides a shiny'-based interactive visualization toolkit for geographically weighted (GW) models. It includes a number of visualization tools, including dynamic mapping of parameter surfaces, statistical visualization, sonification and exporting videos via FFmpeg'.

Gaussian processes are flexible distributions to model functional data. Whilst theoretically appealing, they are computationally cumbersome except for small datasets. This package implements two methods for scaling Gaussian process inference in Stan'. First, a sparse approximation of the likelihood that is generally applicable and, second, an exact method for regularly spaced data modeled by stationary kernels using fast Fourier methods. Utility functions are provided to compile and fit Stan models using the cmdstanr interface. References: Hoffmann and Onnela (2025) <doi:10.18637/jss.v112.i02>.

This package provides ggplot2 geoms analogous to geom_col() and geom_bar() that allow for treemaps using treemapify nested within each bar segment. Also provides geometries for subgroup bordering and text annotation.

This package provides a Bayesian model selection approach for generalized linear mixed models. Currently, GLMMselect can be used for Poisson GLMM and Bernoulli GLMM. GLMMselect can select fixed effects and random effects simultaneously. Covariance structures for the random effects are a product of a unknown scalar and a known semi-positive definite matrix. GLMMselect can be widely used in areas such as longitudinal studies, genome-wide association studies, and spatial statistics. GLMMselect is based on Xu, Ferreira, Porter, and Franck (202X), Bayesian Model Selection Method for Generalized Linear Mixed Models, Biometrics, under review.

Reproducible, programmatic retrieval of datasets from the GESIS Data Archive. The GESIS Data Archive <https://search.gesis.org> makes available thousands of invaluable datasets, but researchers using these datasets are caught in a bind. The archive's terms and conditions bar dissemination of downloaded datasets to third parties, but to ensure that one's work can be reproduced, assessed, and built upon by others, one must provide access to the raw data one has employed. The gesisdata package cuts this knot by providing registered users with programmatic, reproducible access to GESIS datasets from within R'.

Computational intensive calculations for Generalized Additive Models for Location Scale and Shape, <doi:10.1111/j.1467-9876.2005.00510.x>.

This package provides R functions to access the API of the project and repository management web application GitLab'. For many common tasks (repository file access, issue assignment and status, commenting) convenience wrappers are provided, and in addition the full API can be used by specifying request locations. GitLab is open-source software and can be self-hosted or used on <https://about.gitlab.com>.

Provide estimation and data generation tools for a generalization of the transmuted distributions discussed in Shaw and Buckley (2007). See <doi:10.48550/arXiv.0901.0434> for more information.

Tests of goodness-of-fit based on a kernel smoothing of the data. References: Pavà a (2015) <doi:10.18637/jss.v066.c01>.

This package provides functions and analytics for GENEA-compatible accelerometer data into R objects. See topic GENEAread for an introduction to the package. See <https://activinsights.com/technology/geneactiv/> for more details on the GENEActiv device.

It allows running gretl (<http://gretl.sourceforge.net/index.html>) program from R, R Markdown and Quarto. gretl ('Gnu Regression, Econometrics', and Time-series Library) is a statistical software for Econometric analysis. This package does not only integrate gretl and R but also serves as a gretl Knit-Engine for knitr package. Write all your gretl commands in R', R Markdown chunk.

Flexible and robust estimation and inference of Generalised Autoregressive Conditional Heteroscedasticity (GARCH) models with covariates ('X') based on the results by Francq and Thieu (2019) <doi:10.1017/S0266466617000512>. Coefficients can straightforwardly be set to zero by omission, and quasi maximum likelihood methods ensure estimates are generally consistent and inference valid, even when the standardised innovations are non-normal and/or dependent over time. See <doi:10.32614/RJ-2021-057> for an overview of the package.

Designed to simplify geospatial data access from the Statistics Finland Web Feature Service API <https://geo.stat.fi/geoserver/index.html>, the geofi package offers researchers and analysts a set of tools to obtain and harmonize administrative spatial data for a wide range of applications, from urban planning to environmental research. The package contains annually updated time series of municipality key datasets that can be used for data aggregation and language translations.

This package implements functions and instruments for regression model building and its application to forecasting. The main scope of the package is in variables selection and models specification for cases of time series data. This includes promotional modelling, selection between different dynamic regressions with non-standard distributions of errors, selection based on cross validation, solutions to the fat regression model problem and more. Models developed in the package are tailored specifically for forecasting purposes. So as a results there are several methods that allow producing forecasts from these models and visualising them.

The goal of GHCNr is to provide a fast and friendly interface with the Global Historical Climatology Network daily (GHCNd) database, which contains daily summaries of weather station data worldwide (<https://www.ncei.noaa.gov/products/land-based-station/global-historical-climatology-network-daily>). GHCNd is accessed through the web API <https://www.ncei.noaa.gov/access/services/data/v1>. GHCNr main functionalities consist of downloading data from GHCNd, filter it, and to aggregate it at monthly and annual scales.

Datos de nombres inscritos en Chile entre 1920 y 2021, de acuerdo al Servicio de Registro Civil. English: Chilean baby names registered from 1920 to 2021 by the Civil Registry Service.

This package provides functions to generate and analyze data for psychology experiments based on the General Recognition Theory.

It provides an effective, efficient, and fast way to explore the Gene Ontology (GO). Given a set of genes, the package contains functions to assess the GO and obtain the terms associated with the genes and the levels of the GO terms. The package provides functions for the three different GO ontology. We discussed the methods explicitly in the following article <doi:10.1038/s41598-020-73326-3>.

This package implements the Rank In Similarity Graph Edge-count two-sample test (RISE) for high-dimensional and non-Euclidean data. The method constructs similarity-based graphs, such as k-nearest neighbor graph (k-NNG), k-minimum spanning tree (k-MST), and k-minimum distance non-bipartite pairing (k-MDP), and evaluates rank-based within-sample edge counts with asymptotic and permutation p-values. For methodological details, see Zhou and Chen (2023) <https://proceedings.mlr.press/v195/zhou23a.html>.

Selected utilities, in particular geoms and stats functions, extending the ggplot2 package. This package imports functions from EnvStats <doi:10.1007/978-1-4614-8456-1> by Millard (2013), ggpp <https://CRAN.R-project.org/package=ggpp> by Aphalo et al. (2023) and ggstats <doi:10.5281/zenodo.10183964> by Larmarange (2023), and then exports them. This package also contains modified code from ggquickeda <https://CRAN.R-project.org/package=ggquickeda> by Mouksassi et al. (2023) for Kaplan-Meier lines and ticks additions to plots. All functions are tested to make sure that they work reliably.