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This package provides a common interface to allow users to specify a model without having to remember the different argument names across different functions or computational engines (e.g. R, Spark, Stan, etc).
This package provides a wrapper for several FFTW functions. It provides access to the two-dimensional FFT, the multivariate FFT, and the one-dimensional real to complex FFT using the FFTW3 library. The package includes the functions fftw() and mvfftw() which are designed to mimic the functionality of the R functions fft() and mvfft(). The FFT functions have a parameter that allows them to not return the redundant complex conjugate when the input is real data.
This package provides a collection of tools to evaluate probability density functions, cumulative distribution functions, quantile functions and random numbers for truncated random variables. These functions are provided to also compute the expected value and variance. Q-Q plots can be produced. All the probability functions in the stats, stats4 and evd packages are automatically available for truncation.
This package provides a close to zero dependency package to draw and display Venn diagrams up to 7 sets, and any Boolean union of set intersections.
spacefillr enables generation of random and quasi-random space-filling sequences. It supports the following sequences: Halton, Sobol, Owen-scrambled Sobol, Owen-scrambled Sobol with errors distributed as blue noise, progressive jittered, progressive multi-jittered (PMJ), PMJ with blue noise, PMJ02, and PMJ02 with blue noise. The package also includes a C++ API.
This package runs R-code present in a pandoc markdown file and includes the resulting output in the resulting markdown file. This file can then be converted into any of the output formats supported by pandoc. The package can also be used as an engine for writing package vignettes.
This package provides a simple router for your Shiny apps. The router allows you to create dynamic web applications with a real-time User Interface and easily share url to pages within your Shiny apps.
HDF5 is a data model, library and file format for storing and managing large amounts of data. This package provides a nearly feature complete, object oriented wrapper for the HDF5 API using R6 classes. Additionally, functionality is added so that HDF5 objects behave very similar to their corresponding R counterparts.
This package provides qualitative methods for the validation of dynamic models. It contains
an orthogonal set of deviance measures for absolute, relative and ordinal scale and
approaches accounting for time shifts.
The first approach transforms time to take time delays and speed differences into account. The second divides the time series into interval units according to their main features and finds the longest common subsequence (LCS) using a dynamic programming algorithm.
Tools that can be used to reshape and restructure text data.
This package provides functions to compute insolation on tilted surfaces, computes atmospheric transmittance and related parameters such as: Earth radius vector, declination, sunset and sunrise, daylength, equation of time, vector in the direction of the sun, vector normal to surface, and some atmospheric physics.
This package lets you construct paths to your project's files. Use the here function as a drop-in replacement for file.path, it will always locate the files relative to your project root.
The grammar of graphics as implemented in ggplot2 is a poor fit for graph and network visualizations due to its reliance on tabular data input. The ggraph package is an extension of the ggplot2 API tailored to graph visualizations and provides the same flexible approach to building up plots layer by layer.
This package lets you fit generalized linear mixed models for a single grouping factor under maximum likelihood approximating the integrals over the random effects with an adaptive Gaussian quadrature rule; Jose C. Pinheiro and Douglas M. Bates (1995) <doi:10.1080/10618600.1995.10474663>.
This package provides a cross-platform solution to open files, directories or URLs with their associated programs.
This package provides MathJax and macros to enable its use within Rd files for rendering equations in the HTML help files.
This package provides an implementation of the Anderson-Darling GoF test with p-value calculation based on Marsaglia's 2004 paper "Evaluating the Anderson-Darling Distribution".
This package provides a fast dimensionality reduction method scalable to large numbers of samples. Landmark Multi-Dimensional Scaling (LMDS) is an extension of classical Torgerson MDS, but rather than calculating a complete distance matrix between all pairs of samples, only the distances between a set of landmarks and the samples are calculated.
Statistical and biological validation of clustering results. This package implements Dunn Index, Silhouette, Connectivity, Stability, BHI and BSI. Further information can be found in Brock, G et al. (2008) <doi: 10.18637/jss.v025.i04>.
This package provides access to the text shaping functionality in the HarfBuzz library and the bidirectional algorithm in the Fribidi library. This is a low-level utility package mainly for graphic devices that expands upon the font tool-set provided by the systemfonts package.
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.
Compare complex R objects and reveal the key differences. This package was designed particularly for use in testing packages where being able to quickly isolate key differences makes understanding test failures much easier.
This is software accompanying the book 'Applied Smoothing Techniques for Data Analysis---The Kernel Approach with S-Plus Illustrations', Oxford University Press. It provides smoothing methods for nonparametric regression and density estimation
This package provides functions for fitting general linear structural equation models (with observed and latent variables) using the RAM approach, and for fitting structural equations in observed-variable models by two-stage least squares.