Estimate generalized additive mixed models via a version of function gamm from the mgcv package, using the lme4 packagefor estimation.

Lambert W x F distributions are a generalized framework to analyze skewed, heavy-tailed data. It is based on an input/output system, where the output random variable (RV) Y is a non-linearly transformed version of an input RV X ~ F with similar properties as X, but slightly skewed (heavy-tailed). The transformed RV Y has a Lambert W x F distribution. This package contains functions to model and analyze skewed, heavy-tailed data the Lambert Way: simulate random samples, estimate parameters, compute quantiles, and plot/ print results nicely. The most useful function is Gaussianize, which works similarly to scale, but actually makes the data Gaussian. A do-it-yourself toolkit allows users to define their own Lambert W x MyFavoriteDistribution and use it in their analysis right away.

This package provides graphical scales that map data to aesthetics, and provides methods for automatically determining breaks and labels for axes and legends.

This package provides functions and scripts used in the book "Chemometrics with R - Multivariate Data Analysis in the Natural Sciences and Life Sciences" by Ron Wehrens, Springer (2011).

This package lets you use syntax inspired by the package glue to extract matched substrings in a more intuitive and compact way than by using standard regular expressions.

This is yet another command-line argument parser which wraps the powerful Perl module Getopt::Long and with some adaptation for easier use in R. It also provides a simple way for variable interpolation in R.

This package provides tools to enumerates the partitions, unequal partitions, and restricted partitions of an integer; the three corresponding partition functions are also given.

This package provides utilities to help set and record the setting of the seed and the uniform and normal generators used when a random experiment is run. The utilities can be used in other functions that do random experiments to simplify recording and/or setting all the necessary information for reproducibility. See the vignette and reference manual for examples.

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

Query, set, and delete credentials from the git credential store. Manage GitHub tokens and other git credentials. This package is to be used by other packages that need to authenticate to GitHub and/or other git repositories.

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 offers a set of functions for extending dendrogram objects in R, letting you visualize and compare trees of hierarchical clusterings. You can adjust a tree's graphical parameters (the color, size, type, etc of its branches, nodes and labels) and visually and statistically compare different dendrograms to one another.

This package provides a collection of miscellaneous statistical functions for:

• probability distributions,

• probability density estimation,

• most frequent value estimation,

• other statistical measures of location,

• construction of histograms,

• calculation of the Hellinger distance,

• use of classical kernels, and

• univariate piecewise-constant regression.

This package provides an R Shiny application to create visual abstracts for original research. A variety of user defined options and formatting are included.

This package provides tools for the calibration of penalized criteria for model selection. The calibration methods available are based on the slope heuristics.

This package provides probability mass, distribution, quantile, random-variate generation, and method-of-moments parameter-estimation functions for the Delaporte distribution with parameterization based on Vose (2008). The Delaporte is a discrete probability distribution which can be considered the convolution of a negative binomial distribution with a Poisson distribution. Alternatively, it can be considered a counting distribution with both Poisson and negative binomial components. It has been studied in actuarial science as a frequency distribution which has more variability than the Poisson, but less than the negative binomial.

This package provides methods for species distribution modeling, i.e., predicting the environmental similarity of any site to that of the locations of known occurrences of a species.

This package provides methods for manipulating regression models and for describing these in a style adapted for medical journals. It contains functions for generating an HTML table with crude and adjusted estimates, plotting hazard ratio, plotting model estimates and confidence intervals using forest plots, extending this to comparing multiple models in a single forest plots. In addition to the descriptive methods, there are functions for the robust covariance matrix provided by the sandwich package, a function for adding non-linearities to a model, and a wrapper around the Epi package's Lexis() functions for time-splitting a dataset when modeling non-proportional hazards in Cox regressions.

This package allows one to estimate the output of a computer program, as a function of the input parameters, without actually running it. The computer program is assumed to be a Gaussian process, whose parameters are estimated using Bayesian techniques that give a PDF of expected program output. This PDF is conditional on a training set of runs, each consisting of a point in parameter space and the model output at that point. The emphasis is on complex codes that take weeks or months to run, and that have a large number of undetermined input parameters; many climate prediction models fall into this class. The emulator essentially determines Bayesian posterior estimates of the PDF of the output of a model, conditioned on results from previous runs and a user-specified prior linear model. The package includes functionality to evaluate quadratic forms efficiently.

Partial application is the process of reducing the arity of a function by fixing one or more arguments, thus creating a new function lacking the fixed arguments. The curry package provides three different ways of performing partial function application by fixing arguments from either end of the argument list (currying and tail currying) or by fixing multiple named arguments (partial application). This package provides this functionality through the %<%, %-<%, and %><% operators which allows for a programming style comparable to modern functional languages. Compared to other implementations such a purrr::partial() the operators in curry composes functions with named arguments, aiding in autocomplete etc.

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

This package provides data structures that are stored on disk but behave (almost) as if they were in RAM by transparently mapping only a section in main memory.

This package provides simulation methods for the evolution of antibody repertoires. The heavy and light chain variable region of both human and C57BL/6 mice can be simulated in a time-dependent fashion. Both single lineages using one set of V-, D-, and J-genes or full repertoires can be simulated. The algorithm begins with an initial V-D-J recombination event, starting the first phylogenetic tree. Upon completion, the main loop of the algorithm begins, with each iteration representing one simulated time step. Various mutation events are possible at each time step, contributing to a diverse final repertoire.

This package creates D3 JavaScript network, tree, dendrogram, and Sankey graphs from R.