Test Helpers for 'httr2'

Testing and documenting code that communicates with remote servers can be painful. This package helps with writing tests for packages that use 'httr2'. It enables testing all of the logic on the R sides of the API without requiring access to the remote service, and it also allows recording real API responses to use as test fixtures. The ability to save responses and load them offline also enables writing vignettes and other dynamic documents that can be distributed without access to a live server.

Methods for Detection of Clusters in Hierarchical Clustering Dendrograms

Contains methods for detection of clusters in hierarchical clustering dendrograms.

Inter-Widget Interactivity for HTML Widgets

Provides building blocks for allowing HTML widgets to communicate with each other, with Shiny or without (i.e. static .html files). Currently supports linked brushing and filtering.

Tools for Social Network Analysis

A range of tools for social network analysis, including node and graph-level indices, structural distance and covariance methods, structural equivalence detection, network regression, random graph generation, and 2D/3D network visualization.

Scans R Projects for Vulnerable Third Party Dependencies

Collects a list of your third party R packages, and scans them with the 'OSS' Index provided by 'Sonatype', reporting back on any vulnerabilities that are found in the third party packages you use.

Methods for Changepoint Detection

Implements various mainstream and specialised changepoint methods for finding single and multiple changepoints within data. Many popular non-parametric and frequentist methods are included. The cpt.mean(), cpt.var(), cpt.meanvar() functions should be your first point of call.

Integrating Phylogenies and Ecology

Functions for phylocom integration, community analyses, null-models, traits and evolution. Implements numerous ecophylogenetic approaches including measures of community phylogenetic and trait diversity, phylogenetic signal, estimation of trait values for unobserved taxa, null models for community and phylogeny randomizations, and utility functions for data input/output and phylogeny plotting. A full description of package functionality and methods are provided by Kembel et al. (2010) .

Various R Programming Tools

Functions to assist in R programming, including: - assist in developing, updating, and maintaining R and R packages ('ask', 'checkRVersion', 'getDependencies', 'keywords', 'scat'), - calculate the logit and inverse logit transformations ('logit', 'inv.logit'), - test if a value is missing, empty or contains only NA and NULL values ('invalid'), - manipulate R's .Last function ('addLast'), - define macros ('defmacro'), - detect odd and even integers ('odd', 'even'), - convert strings containing non-ASCII characters (like single quotes) to plain ASCII ('ASCIIfy'), - perform a binary search ('binsearch'), - sort strings containing both numeric and character components ('mixedsort'), - create a factor variable from the quantiles of a continuous variable ('quantcut'), - enumerate permutations and combinations ('combinations', 'permutation'), - calculate and convert between fold-change and log-ratio ('foldchange', 'logratio2foldchange', 'foldchange2logratio'), - calculate probabilities and generate random numbers from Dirichlet distributions ('rdirichlet', 'ddirichlet'), - apply a function over adjacent subsets of a vector ('running'), - modify the TCP_NODELAY ('de-Nagle') flag for socket objects, - efficient 'rbind' of data frames, even if the column names don't match ('smartbind'), - generate significance stars from p-values ('stars.pval'), - convert characters to/from ASCII codes ('asc', 'chr'), - convert character vector to ASCII representation ('ASCIIfy'), - apply title capitalization rules to a character vector ('capwords').

Biased Urn Model Distributions

Statistical models of biased sampling in the form of univariate and multivariate noncentral hypergeometric distributions, including Wallenius' noncentral hypergeometric distribution and Fisher's noncentral hypergeometric distribution. See vignette("UrnTheory") for explanation of these distributions. Literature: Fog, A. (2008a). Calculation Methods for Wallenius' Noncentral Hypergeometric Distribution, Communications in Statistics, Simulation and Computation, 37(2) . Fog, A. (2008b). Sampling methods for Wallenius’ and Fisher’s noncentral hypergeometric distributions, Communications in Statistics—Simulation and Computation, 37(2) .

Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Related Algorithms

A fast reimplementation of several density-based algorithms of the DBSCAN family. Includes the clustering algorithms DBSCAN (density-based spatial clustering of applications with noise) and HDBSCAN (hierarchical DBSCAN), the ordering algorithm OPTICS (ordering points to identify the clustering structure), shared nearest neighbor clustering, and the outlier detection algorithms LOF (local outlier factor) and GLOSH (global-local outlier score from hierarchies). The implementations use the kd-tree data structure (from library ANN) for faster k-nearest neighbor search. An R interface to fast kNN and fixed-radius NN search is also provided. Hahsler, Piekenbrock and Doran (2019) .