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This package contains genomic data for the plant pathogen Phytophthora infestans. It includes a variant file, a sequence file and an annotation file. This package is intended to be used as example data for packages that work with genomic data.
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 a simple set of wrapper functions for data.table::fread() that allows subsetting or filtering rows and selecting columns of table-formatted files too large for the available RAM.
This package provides an implementation of efficient approximate leave-one-out (LOO) cross-validation for Bayesian models fit using Markov chain Monte Carlo, as described in doi:10.1007/s11222-016-9696-4. The approximation uses Pareto smoothed importance sampling (PSIS), a new procedure for regularizing importance weights. As a byproduct of the calculations, we also obtain approximate standard errors for estimated predictive errors and for the comparison of predictive errors between models. The package also provides methods for using stacking and other model weighting techniques to average Bayesian predictive distributions.
Functions for modelling that help you seamlessly integrate modelling into a pipeline of data manipulation and visualisation.
This package provides helper functions to install and maintain the LaTeX distribution named TinyTeX, a lightweight, cross-platform, portable, and easy-to-maintain version of TeX Live. This package also contains helper functions to compile LaTeX documents, and install missing LaTeX packages automatically.
The main function archetypes implements a framework for archetypal analysis supporting arbitrary problem solving mechanisms for the different conceptual parts of the algorithm.
This package provides a command line parser inspired by Python's optparse library to be used with Rscript to write shebang scripts that accept short and long options.
Circular Statistics, from "Topics in Circular Statistics" (2001) S. Rao Jammalamadaka and A. SenGupta, World Scientific.
This package provides functions for importing, exporting, plotting and other manipulations of bitmapped images.
Flexibly restructure and aggregate data using just two functions: melt and cast. This package provides them.
This package provides tools for the statistical modelling of spatial extremes using max-stable processes, copula or Bayesian hierarchical models. More precisely, this package allows (conditional) simulations from various parametric max-stable models, analysis of the extremal spatial dependence, the fitting of such processes using composite likelihoods or least square (simple max-stable processes only), model checking and selection and prediction.
This package provides tools for clustering and principal component analysis (with robust methods, and parallelized functions).
This package contains data structures and algorithms for sparse arrays and matrices, based on index arrays and simple triplet representations, respectively.
This package provides a collection of functions dealing with labelled data, like reading and writing data between R and other statistical software packages. This includes easy ways to get, set or change value and variable label attributes, to convert labelled vectors into factors or numeric (and vice versa), or to deal with multiple declared missing values.
This package provides different approaches for selecting the threshold in generalized Pareto distributions. Most of them are based on minimizing the AMSE-criterion or at least by reducing the bias of the assumed GPD-model. Others are heuristically motivated by searching for stable sample paths, i.e. a nearly constant region of the tail index estimator with respect to k, which is the number of data in the tail. The third class is motivated by graphical inspection. In addition, a sequential testing procedure for GPD-GoF-tests is also implemented here.
This package contains all the datasets for the spatstat package.
This package provides 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 (also called extended hypergeometric distribution).
This package provides a set of predicates and assertions for checking the types of variables. This is mainly for use by other package developers who want to include run-time testing features in their own packages.
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.
The Datasaurus Dozen is a set of datasets with the same summary statistics. They retain the same summary statistics despite having radically different distributions. The datasets represent a larger and quirkier object lesson that is typically taught via Anscombe's Quartet (available in the 'datasets' package). Anscombe's Quartet contains four very different distributions with the same summary statistics and as such highlights the value of visualisation in understanding data, over and above summary statistics. As well as being an engaging variant on the Quartet, the data is generated in a novel way. The simulated annealing process used to derive datasets from the original Datasaurus is detailed in "Same Stats, Different Graphs: Generating Datasets with Varied Appearance and Identical Statistics through Simulated Annealing" doi:10.1145/3025453.3025912.
The labeling package provides a range of axis labeling algorithms.
This is a package for pretty-printing R code without changing the user's formatting intent.
The package provides estimators of the mode of univariate unimodal (and sometimes multimodal) data and values of the modes of usual probability distributions.