This package provides a collection of lexical hash tables, dictionaries, and word lists.

This package contains an efficient implementation of Sen's slope method (Sen, 1968) plus implementation of Xuebin Zhang's (Zhang, 1999) and Yue-Pilon's (Yue, 2002) pre-whitening approaches to determining trends in climate data.

This package provides response time distributions (density/PDF, distribution function/CDF, quantile function, and random generation):

• Ratcliff diffusion model (Ratcliff & McKoon, 2008, <doi:10.1162/neco.2008.12-06-420>) based on C code by Andreas and Jochen Voss and

• linear ballistic accumulator (LBA; Brown & Heathcote, 2008, <doi:10.1016/j.cogpsych.2007.12.002>) with different distributions underlying the drift rate.

This package provides statistical procedures for calculating population-mean cosinor, non-stationary cosinor, estimation of best-fitting period, tests of population rhythm differences and more.

This package offers methods to perform asymptotically bias-corrected regularized linear discriminant analysis (ABC_RLDA) for cost-sensitive binary classification. The bias-correction is an estimate of the bias term added to regularized discriminant analysis that minimizes the overall risk.

This package provides simple and crisp publication-quality graphics for the ExPosition family of packages. See An ExPosition of the Singular Value Decomposition in R (Beaton et al 2014) <doi:10.1016/j.csda.2013.11.006>.

This package provides HTTP error helpers. Methods are included for general purpose HTTP error handling, as well as individual methods for every HTTP status code, both via status code numbers as well as their descriptive names. It supports the ability to adjust behavior to stop, message or warning. It includes the ability to use a custom whisker template to have any configuration of status code, short description, and verbose message.

This package provides tools for the analysis and visualization of bilateral asymmetry in parasitic infections.

This package provides a variety of descriptive multivariate analyses with the singular value decomposition, such as principal components analysis, correspondence analysis, and multidimensional scaling. See An ExPosition of the Singular Value Decomposition in R (Beaton et al 2014) <doi:10.1016/j.csda.2013.11.006>.

This package provides a dplyr back end for databases that allows you to work with remote database tables as if they are in-memory data frames. Basic features works with any database that has a DBI back end; more advanced features require SQL translation to be provided by the package author.

This package provides classes and methods for spatial data; the classes document where the spatial location information resides, for 2D or 3D data. Utility functions are provided, e.g. for plotting data as maps, spatial selection, as well as methods for retrieving coordinates, for subsetting, print, summary, etc.

Create and manage unique directories for each TensorFlow training run. This package provides a unique, time stamped directory for each run along with functions to retrieve the directory of the latest run or latest several runs.

This package provides a statistical method to impute the missing values in accelerometer data. The methodology includes both parametric and semi-parametric multiple imputations under the zero-inflated Poisson lognormal model. It also provides multiple functions to preprocess the accelerometer data previous to the missing data imputation. These include detecting the wearing and the non-wearing time, selecting valid days and subjects, and creating plots.

This package adds distinctive yet unobtrusive geometric patterns where solid color fills are normally used. Patterned figures look just as professional when viewed by colorblind readers or when printed in black and white. The dozen included patterns can be customized in terms of scale, rotation, color, fill, line type, and line width. It is compatible with the ggplot2 package as well as grid graphics.

This package provides useful functions to edit ggplot object (e.g., setting fonts for theme and layers, adding rounded rectangle as background for each of the legends).

This package provides an R implementation of the Octave package signal, containing a variety of signal processing tools, such as signal generation and measurement, correlation and convolution, filtering, filter design, filter analysis and conversion, power spectrum analysis, system identification, decimation and sample rate change, and windowing.

This is a package containing Public Key Infrastructure functions such as verifying certificates, RSA encryption and signing, which can be used to build PKI infrastructure and perform cryptographic tasks.

This package provides an extension to the Shiny web application framework for R, making it easy to create attractive dashboards.

This package allows the estimation of hierarchical F-statistics from haploid or diploid genetic data with any numbers of levels in the hierarchy, following the algorithm of Yang (Evolution, 1998, 52(4):950-956). Functions are also given to test via randomisations the significance of each F and variance components, using the likelihood-ratio statistics G.

This package provides an interface to Amazon Web Services networking and content delivery services, including Route 53 Domain Name System service, CloudFront content delivery, load balancing, and more.

This package analyzes gene expression (time series) data with focus on the inference of gene networks. In particular, GeneNet implements the methods of Schaefer and Strimmer (2005a,b,c) and Opgen-Rhein and Strimmer (2006, 2007) for learning large-scale gene association networks (including assignment of putative directions).

This package provides 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.

This package offers extensive tools for phylogenetic analysis. It focuses on phylogenetic comparative biology but also includes methods for visualizing, analyzing, manipulating, reading, writing, and inferring phylogenetic trees. Functions for comparative biology include ancestral state reconstruction, model fitting, and phylogeny and trait data simulation. A broad range of plotting methods includes mapping trait evolution on trees, projecting trees into phenotype space or geographic maps, and visualizing correlated speciation between trees. Additional functions allow for reading, writing, analyzing, inferring, simulating, and manipulating phylogenetic trees and comparative data. Examples include computing consensus trees, simulating trees and data under various models, and attaching species or clades to a tree either randomly or non-randomly. This package provides numerous tools for tree manipulations and analyses that are valuable for phylogenetic research.

This package tests the goodness of fit of a distribution of offspring to the Normal, Poisson, and Gamma distribution and estimates the proportional paternity of the second male (P2) based on the best fit distribution.