Streaming JSON (ndjson) has one JSON record per-line and many modern ndjson files contain large numbers of records. These constructs may not be columnar in nature, but it is often useful to read in these files and "flatten" the structure out to enable working with the data in an R data.frame-like context. Functions are provided that make it possible to read in plain ndjson files or compressed (gz) ndjson files and either validate the format of the records or create "flat" data.table structures from them.

Tidygeocoder makes getting data from geocoding services easy. A unified high-level interface is provided for a selection of supported geocoding services and results are returned in tibble format.

The function missForest in this package is used to impute missing values, particularly in the case of mixed-type data. It uses a random forest trained on the observed values of a data matrix to predict the missing values. It can be used to impute continuous and/or categorical data, including complex interactions and non-linear relations. It yields an OOB imputation error estimate without the need of a test set or elaborate cross- validation. It can be run in parallel to save computation time.

This package provides the dyn class interfaces ts, irts, zoo and zooreg time series classes to lm, glm, loess, quantreg::rq, MASS::rlm, MCMCpack::MCMCregress(), quantreg::rq(), randomForest::randomForest() and other regression functions, allowing those functions to be used with time series including specifications that may contain lags, diffs and missing values.

This package implements many algorithms for statistical learning on sparse matrices: matrix factorizations, matrix completion, elastic net regressions, factorization machines. The rsparse package also enhances the Matrix package by providing methods for multithreaded <sparse, dense> matrix products and native slicing of the sparse matrices in Compressed Sparse Row (CSR) format.

This package provides a collection of functions to explore and to investigate basic properties of financial returns and related quantities. The covered fields include techniques of explorative data analysis and the investigation of distributional properties, including parameter estimation and hypothesis testing. Even more, there are several utility functions for data handling and management.

This package provides C code used by the wmtsa, fractal, and sapa R packages.

This package provides tools to compute Gower's distance (or similarity) coefficient between records, and to compute the top-n matches between records. Core algorithms are executed in parallel on systems supporting OpenMP.

This package provides functions for kernel-regression-based association tests including Burden test, SKAT and SKAT-O. These methods aggregate individual SNP score statistics in a SNP set and efficiently compute SNP-set level p-values.

This package provides functions for Constraint Based Simulation using Flux Balance Analysis and informative analysis of the data generated during simulation.

This R package provides a single procedure guix.install(), which allows users to install R packages via Guix right from within their running R session. If the requested R package does not exist in Guix at this time, the package and all its missing dependencies will be imported recursively and the generated package definitions will be written to ~/.Rguix/packages.scm. This record of imported packages can be used later to reproduce the environment, and to add the packages in question to a proper Guix channel (or Guix itself). guix.install() not only supports installing packages from CRAN, but also from Bioconductor or even arbitrary git or mercurial repositories, replacing the need for installation via devtools.

This package provides tools to identify and read BMP, JPEG, PNG, and TIFF format bitmap images. Identification defaults to the use of the magic number embedded in the file rather than the file extension.

This is a package for visualizing functional data and identifying functional outliers with bagplots, boxplots and rainbow plots.

Similarity Network Fusion takes multiple views of a network and fuses them together to construct an overall status matrix. The input to our algorithm can be feature vectors, pairwise distances, or pairwise similarities. The learned status matrix can then be used for retrieval, clustering, and classification.

This package provides functions for creating plots and image files in a unified way regardless of output format (EPS, PDF, PNG, SVG, TIFF, WMF, etc.). Default device options as well as scales and aspect ratios are controlled in a uniform way across all device types. Switching output format requires minimal changes in code. This package is ideal for large-scale batch processing, because it will never leave open graphics devices or incomplete image files behind, even on errors or user interrupts.

This package provides tools to compares k samples using the Anderson-Darling test, Kruskal-Wallis type tests with different rank score criteria, Steel's multiple comparison test, and the Jonckheere-Terpstra (JT) test. It computes asymptotic, simulated or (limited) exact P-values, all valid under randomization, with or without ties, or conditionally under random sampling from populations, given the observed tie pattern. Except for Steel's test and the JT test it also combines these tests across several blocks of samples.

This package enhances the R Optimization Infrastructure (ROI) package with a connection to the neos server. ROI optimization problems can directly be sent to the neos server and solution obtained in the typical ROI style.

This package provides data structures and basic operations for ordinary sets, generalizations such as fuzzy sets, multisets, and fuzzy multisets, customizable sets, and intervals.

Solve optimal transport problems. Compute Wasserstein distances (a.k.a. Kantorovitch, Fortet--Mourier, Mallows, Earth Mover's, or minimal L_p distances), return the corresponding transference plans, and display them graphically. Objects that can be compared include grey-scale images, (weighted) point patterns, and mass vectors.

This package provides a complete unit test system and functions to implement its GUI part.

This package provides functions for reading and writing data stored by some versions of Epi Info, Minitab, S, SAS, SPSS, Stata, Systat and Weka and for reading and writing some dBase files.

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.

This package provides bindings to the OSQP solver. The OSQP solver is a numerical optimization package or solving convex quadratic programs written in C and based on the alternating direction method of multipliers. See <arXiv:1711.08013> for details.

This package provides some methods to manipulate HDF5 files, extending the hdf5r package. Reading and writing R objects to HDF5 formats follow the specification of AnnData.