This package contains supporting data sets that are used in other packages maintained by Torsten Hothorn.

This package can be used to predict the r-species accumulation curve (r-SAC), which is the number of species represented at least r times as a function of the sampling effort. When r = 1, the curve is known as the species accumulation curve, or the library complexity curve in high-throughput genomic sequencing. The package includes both parametric and nonparametric methods, as described by Deng C, et al. (2018).

This package provides a fast implementation of hierarchical clustering.

This package provides a toolset for Geometric Morphometrics and mesh processing. This includes (among other stuff) mesh deformations based on reference points, permutation tests, detection of outliers, processing of sliding semi-landmarks and semi-automated surface landmark placement.

This package implements tools designed to collect and organize Twitter data via Twitter's REST and stream Application Program Interfaces (API).

This package provides simple functions to compute and plot two types (sample-size- and coverage-based) rarefaction and extrapolation curves for species diversity (Hill numbers) based on individual-based abundance data or sampling-unit- based incidence data; see Chao and others (2014, Ecological Monographs) for pertinent theory and methodologies, and Hsieh, Ma and Chao (2016, Methods in Ecology and Evolution) for an introduction of the R package.

This package allows you to render vector-based SVG images into high-quality custom-size bitmap arrays using the librsvg2 library. The resulting bitmap can be written to e.g. PNG, JPEG or WEBP format. In addition, the package can convert images directly to various formats such as PDF or PostScript.

This package extends the grammar of graphics as implemented by ggplot2 to include the description of animation. It does this by providing a range of new grammar classes that can be added to the plot object in order to customise how it should change with time.

This is an extension of the testthat package that lets you add parameters to your unit tests. Parameterized unit tests are often easier to read and more reliable, since they follow the DNRY (do not repeat yourself) rule.

This package handles very large numbers in R. Real numbers are held using their natural logarithms, plus a logical flag indicating sign. The package includes a vignette that gives a step-by-step introduction to using S4 methods.

This is a package for curve, surface and function fitting with an emphasis on splines, spatial data and spatial statistics. The major methods include cubic, and thin plate splines, Kriging, and compactly supported covariance functions for large data sets.

This package provides a set of predicates and assertions for checking the properties of files and connections. This is mainly for use by other package developers who want to include run-time testing features in their own packages.

This package contains several basic utility functions including: moving (rolling, running) window statistic functions, read/write for GIF and ENVI binary files, fast calculation of AUC, LogitBoost classifier, base64 encoder/decoder, round-off-error-free sum and cumsum, etc.

This package provides a collection of clean R Markdown HTML document templates using classless CSS styles. These documents use a minimal set of dependencies but still look great, making them suitable for use a package vignettes or for sharing results via email.

This package provides an R wrapper for libnabo, an exact or approximate k nearest neighbour library which is optimised for low dimensional spaces (e.g. 3D). nabor includes a knn function that is designed as a drop-in replacement for the RANN function nn2. In addition, objects which include the k-d tree search structure can be returned to speed up repeated queries of the same set of target points.

This package provides a general purpose toolbox for personality, psychometric theory and experimental psychology. Functions are primarily for multivariate analysis and scale construction using factor analysis, principal component analysis, cluster analysis and reliability analysis, although others provide basic descriptive statistics. Item Response Theory is done using factor analysis of tetrachoric and polychoric correlations. Functions for analyzing data at multiple levels include within and between group statistics, including correlations and factor analysis. Functions for simulating and testing particular item and test structures are included. Several functions serve as a useful front end for structural equation modeling. Graphical displays of path diagrams, factor analysis and structural equation models are created using basic graphics.

This package provides tools to calculate exact and approximate theory experimental designs for D, A, and I criteria. Very large designs may be created. Experimental designs may be blocked or blocked designs created from a candidate list, using several criteria. The blocking can be done when whole and within plot factors interact.

This is an R package for spell checking common document formats including LaTeX, markdown, manual pages, and DESCRIPTION files. It includes utilities to automate checking of documentation and vignettes as a unit test during R CMD check. Both British and American English are supported out of the box and other languages can be added. In addition, packages may define a wordlist to allow custom terminology without having to abuse punctuation.

This package provides functions to convert a page of plots drawn with the graphics package into identical output drawn with the grid package. The result looks like the original graphics-based plot, but consists of grid grobs and viewports that can then be manipulated with grid functions (e.g., edit grobs and revisit viewports).

This package computes standardized mean differences and confidence intervals for multiple data types based on Yang, D., & Dalton, J. E. (2012) <https://support.sas.com/resources/papers/proceedings12/335-2012.pdf>.

This package provides classes and methods for dense and sparse matrices and operations on them using LAPACK and SuiteSparse.

This package provides a toolset for functional enrichment analysis and visualization, gene/protein/SNP identifier conversion and mapping orthologous genes across species via g:Profiler. The main tools are:

1. g:GOSt, functional enrichment analysis and visualization of gene lists;

2. g:Convert, gene/protein/transcript identifier conversion across various namespaces;

3. g:Orth, orthology search across species;

4. g:SNPense, mapping SNP rs identifiers to chromosome positions, genes and variant effects.

This package is an R interface corresponding to the 2019 update of g:Profiler and provides access to versions e94_eg41_p11 and higher.

This package provides a collection of dimensionality reduction techniques from R packages and provides a common interface for calling the methods.

Similarly to the FNN package, this package allows calculation of the k nearest neighbors (kNN) of a data matrix. The implementation is based on cover trees introduced by Alina Beygelzimer, Sham Kakade, and John Langford (2006) doi:10.1145/1143844.1143857.