This is a package for constructing minimum-cost regular spanning subgraph as part of a non-parametric two-sample test for equality of distribution.

This package provides an R interface to Google's BigQuery database.

This package is a micro-package for getting your IP address, either the local/internal or the public/external one. Currently only IPv4 addresses are supported.

This package implements multiple imputation for multivariate panel or clustered data.

This package provides the exponential integrals E_1(x), E_2(x), E_n(x) and Ei(x), and the incomplete gamma function G(a, x) defined for negative values of its first argument. The package also gives easy access to the underlying C routines through an API; see the package vignette for details.

This package provides an R wrapper of OpenAI API endpoints (see https://platform.openai.com/docs/introduction for details). This package covers Models, Completions, Chat, Edits, Images, Embeddings, Audio, Files, Fine-tunes, Moderations, and legacy Engines endpoints.

This package provides functions for reading, writing, plotting, analysing, and manipulating allelic and haplotypic data, including from VCF files, and for the analysis of population nucleotide sequences and micro-satellites including coalescent analyses, linkage disequilibrium, population structure (Fst, Amova) and equilibrium (HWE), haplotype networks, minimum spanning tree and network, and median-joining networks.

This package provides a ggplot2 extension that enables the rendering of complex formatted plot labels (titles, subtitles, facet labels, axis labels, etc.). Text boxes with automatic word wrap are also supported.

This package provides an interface to Amazon Web Services cost management services, including cost and usage reports, budgets, pricing, and more.

This package provides a toolkit of functions for nonlinear regression and repeated measurements. It was designated to be imported by other packages such as gnlm, stable, growth, repeated, and event.

This package provides tidy tools for quantifying how well a model fits to a data set such as confusion matrices, class probability curve summaries, and regression metrics (e.g., RMSE).

This package provides a fast reimplementation of several density-based algorithms of the DBSCAN family. It includes the clustering algorithms DBSCAN (density-based spatial clustering of applications with noise) and hierarchical DBSCAN (HDBSCAN), the ordering algorithm ordering points to identify the clustering structure (OPTICS), shared nearest neighbor clustering, and the outlier detection algorithms local outlier factor (LOF) and global-local outlier score from hierarchies (GLOSH). The implementations use the kd-tree data structure for faster k-nearest neighbor search. An R interface to fast kNN and fixed-radius NN search is also provided.

r-selectr translates a CSS3 selector into an equivalent XPath expression. This allows you to use CSS selectors when working with the XML package as it can only evaluate XPath expressions. Also provided are convenience functions useful for using CSS selectors on XML nodes. This package is a port of the Python package cssselect.

This package provides a set of tools for inspecting and understanding R data structures inspired by str. It includes ast for visualizing abstract syntax trees, ref for showing shared references, cst for showing call stack trees, and obj_size for computing object sizes.

The main function archetypes implements a framework for archetypal analysis supporting arbitrary problem solving mechanisms for the different conceptual parts of the algorithm.

Format dates and times flexibly and to whichever locales make sense. This package parses dates, times, and date-times in various formats (including string-based ISO 8601 constructions). The formatting syntax gives the user many options for formatting the date and time output in a precise manner. Time zones in the input can be expressed in multiple ways and there are many options for formatting time zones in the output as well. Several of the provided helper functions allow for automatic generation of locale-aware formatting patterns based on date/time skeleton formats and standardized date/time formats with varying specificity.

This package provides fast and accurate convolution-type smoothed quantile regression, implemented using Barzilai-Borwein gradient descent with a Huber regression warm start. Confidence intervals for regression coefficients are constructed using multiplier bootstrap.

This package contains various tools for working with and evaluating cross-validated area under the ROC curve (AUC) estimators. The primary functions of the package are ci.cvAUC and ci.pooled.cvAUC, which report cross-validated AUC and compute confidence intervals for cross-validated AUC estimates based on influence curves for i.i.d. and pooled repeated measures data, respectively.

This package provides a menu-driven program and library of functions for carrying out convergence diagnostics and statistical and graphical analysis of Markov chain Monte Carlo (MCMC) sampling output.

This package provides a close to zero dependency package to draw and display Venn diagrams up to 7 sets, and any Boolean union of set intersections.

Learn vector representations of sentences, paragraphs or documents by using the Paragraph Vector algorithms, namely the distributed bag of words (PV-DBOW) and the distributed memory (PV-DM) model. Top2vec finds clusters in text documents by combining techniques to embed documents and words and density-based clustering. It does this by embedding documents in the semantic space as defined by the doc2vec algorithm. Next it maps these document embeddings to a lower-dimensional space using the Uniform Manifold Approximation and Projection (UMAP) clustering algorithm and finds dense areas in that space using a Hierarchical Density-Based Clustering technique (HDBSCAN). These dense areas are the topic clusters which can be represented by the corresponding topic vector which is an aggregate of the document embeddings of the documents which are part of that topic cluster. In the same semantic space similar words can be found which are representative of the topic.

This method identifies topological domains in genomes from Hi-C sequence data. The authors published an implementation of their method as an R script. This package originates from those original TopDom R scripts and provides help pages adopted from the original TopDom PDF documentation. It also provides a small number of bug fixes to the original code.

This package adds additional Twitter Bootstrap components to Shiny.

This package provides a set of tools for the statistical analysis of data using:

1. normal linear models;

2. generalized linear models;

3. negative binomial regression models as alternative to the Poisson regression models under the presence of overdispersion;

4. beta-binomial and random-clumped binomial regression models as alternative to the binomial regression models under the presence of overdispersion;

5. zero-inflated and zero-altered regression models to deal with zero-excess in count data;

6. generalized nonlinear models;

7. generalized estimating equations for cluster correlated data.