This package provides a common framework for optimization of black-box functions for other packages, e.g. mlr3. It offers various optimization methods e.g. grid search, random search and generalized simulated annealing.

Solving a system of linear equations is one of the most fundamental computational problems for many fields of mathematical studies, such as regression problems from statistics or numerical partial differential equations. This package provides basic stationary iterative solvers such as Jacobi, Gauss-Seidel, Successive Over-Relaxation and SSOR methods. Nonstationary, also known as Krylov subspace methods are also provided. Sparse matrix computation is also supported in that solving large and sparse linear systems can be manageable using the Matrix package along with RcppArmadillo.

This package contains a list of functional time series, sliced functional time series, and functional data sets. Functional time series is a special type of functional data observed over time. Sliced functional time series is a special type of functional time series with a time variable observed over time.

This package provides R bindings to OpenSSL libssl and libcrypto, plus custom SSH pubkey parsers. It supports RSA, DSA and NIST curves P-256, P-384 and P-521. Cryptographic signatures can either be created and verified manually or via x509 certificates. AES block cipher is used in CBC mode for symmetric encryption; RSA for asymmetric (public key) encryption. High-level envelope functions combine RSA and AES for encrypting arbitrary sized data. Other utilities include key generators, hash functions (md5, sha1, sha256, etc), base64 encoder, a secure random number generator, and bignum math methods for manually performing crypto calculations on large multibyte integers.

The main purpose of this package is to provide the algorithmic complexity for short strings, an approximation of the Kolmogorov Complexity of a short string using the coding theorem method. While the database containing the complexity is provided in the data only package acss.data, this package provides functions accessing the data such as prob_random returning the posterior probability that a given string was produced by a random process. In addition, two traditional (but problematic) measures of complexity are also provided: entropy and change complexity.

This package provides an mlr3 extension that provides various resampling-based confidence interval (CI) methods for estimating the generalization error. These CI methods are implemented as mlr3 measures, enabling the evaluation of individual algorithms on specific tasks as well as the comparison of different learning algorithms.

This package provides flexible Bayesian estimation of IMIFA and related models, for nonparametrically clustering high-dimensional data. The IMIFA model conducts Bayesian nonparametric model-based clustering with factor analytic covariance structures without recourse to model selection criteria to choose the number of clusters or cluster-specific latent factors, mostly via efficient Gibbs updates. Model-specific diagnostic tools are also provided, as well as many options for plotting results, conducting posterior inference on parameters of interest, posterior predictive checking, and quantifying uncertainty.

Webshot makes it easy to take screenshots of web pages from within R. It can also run Shiny applications locally and take screenshots of the application; and it can render and screenshot static as well as interactive R Markdown documents.

This package provides tools for the analysis of high-dimensional data developed/implemented at the group "Statistical Complexity Reduction In Molecular Epidemiology" (SCRIME). The main focus is on SNP data, but most of the functions can also be applied to other types of categorical data.

Functions and examples are provided for transmission/disequilibrium tests for extended marker haplotypes, as in Clayton, D. and Jones, H. (1999) "Transmission/disequilibrium tests for extended marker haplotypes".

How fast can you type R functions on your keyboard? Find out by running a zty.pe game: export R functions as instructions to type to destroy opponents' vessels.

This package provides methods and tools for displaying and analysing univariate time series forecasts including exponential smoothing via state space models and automatic ARIMA modelling.

This package provides a replacement for the extract function from the raster package that is suitable for extracting raster values using sf polygons.

This package implements time series clustering along with optimized techniques related to the dynamic time warping distance and its corresponding lower bounds. The implementations of partitional, hierarchical, fuzzy, k-Shape and TADPole clustering are available. Functionality can be easily extended with custom distance measures and centroid definitions. Implementations of DTW barycenter averaging, a distance based on global alignment kernels, and the soft-DTW distance and centroid routines are also provided. All included distance functions have custom loops optimized for the calculation of cross-distance matrices, including parallelization support. Several cluster validity indices are included.

This package provides a %<-% operator to perform multiple, unpacking, and destructuring assignment in R. The operator unpacks the right-hand side of an assignment into multiple values and assigns these values to variables on the left-hand side of the assignment.

This package contains utility functions for the spatstat package which may also be useful for other purposes.

This started out as a package for file and string manipulation. Since then, the fs and strex packages emerged, offering functionality previously given by this package. Those packages have hence almost pushed filesstrings into extinction. However, it still has a small number of unique, handy file manipulation functions which can be seen in the vignette. One example is a function to remove spaces from all file names in a directory.

This package provides a header-only C++ library is provided with support for dates, time zones, ISO weeks, Julian dates, and Islamic dates. date offers extensive date and time functionality for the C++11, C++14 and C++17 standards. A slightly modified version has been accepted (along with tz.h) as part of C++20. This package regroups all header files from the upstream repository so that other R packages can use them in their C++ code.

This package provides a set of psychometric tools for cognitive diagnosis modeling based on the generalized deterministic inputs, noisy and gate (G-DINA) model by de la Torre (2011) doi:10.1007/s11336-011-9207-7 and its extensions, including the sequential G-DINA model by Ma and de la Torre (2016) doi:10.1111/bmsp.12070 for polytomous responses, and the polytomous G-DINA model by Chen and de la Torre doi:10.1177/0146621613479818 for polytomous attributes. Joint attribute distribution can be independent, saturated, higher-order, loglinear smoothed or structured. Q-matrix validation, item and model fit statistics, model comparison at test and item level and differential item functioning can also be conducted. A graphical user interface is also provided.

This package provides an interface (wrapper) to MPI APIs. It also provides an interactive R manager and worker environment.

Miscellaneous functions commonly used by YuLab-SMU, such as install_zip_gh to install R packages from Github ZIP files.

latex2exp parses and converts LaTeX math formulas to R's plotmath expressions, used to enter mathematical formulas and symbols to be rendered as text, axis labels, etc. throughout R's plotting system.

This package provides S3 classes and methods for one-dimensional normal mixture models, for, e.g., density estimation or clustering algorithms research and teaching; it provides the widely used Marron-Wand densities. It also provides tools for efficient random number generation and graphics.

This package provides a forest plot that allows for multiple confidence intervals per row, custom fonts for each text element, custom confidence intervals, text mixed with expressions, and more. The aim is to extend the use of forest plots beyond meta-analyses. This is a more general version of the original rmeta package's forestplot() function and relies heavily on the grid package.