This package provides a collection of functions to create spatial weights matrix objects from polygon contiguities, from point patterns by distance and tessellations, for summarizing these objects, and for permitting their use in spatial data analysis, including regional aggregation by minimum spanning tree.

This package lets you create a reproducible ggplot2 object by storing the data and calls.

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 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 fast and memory-friendly tools for text vectorization, topic modeling (LDA, LSA), word embeddings (GloVe), similarities. It provides a source-agnostic streaming API, which allows researchers to perform analysis of collections of documents which are larger than available RAM. All core functions are parallelized to benefit from multicore machines.

This package simulates continuous distributions of random vectors using Markov chain Monte Carlo (MCMC). Users specify the distribution by an R function that evaluates the log unnormalized density. Algorithms are random walk Metropolis algorithm (function metrop), simulated tempering (function temper), and morphometric random walk Metropolis (function morph.metrop), which achieves geometric ergodicity by change of variable.

This package provides exploratory data analysis methods to summarize, visualize and describe datasets. The main principal component methods are available, those with the largest potential in terms of applications: principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, Multiple Factor Analysis when variables are structured in groups, etc. and hierarchical cluster analysis.

This package is a data visualization package for R providing an implementation of an interactive grammar of graphics, taking the best parts of ggplot2, combining them with the reactive framework of Shiny and drawing web graphics using Vega.

This package is a port of the gWidgets2 API for the tcltk package.

This package provides functions relating to time series analysis and computational finance.

This package provides a set of R functions for identifying and correcting HGNC human gene symbols. In addition, you can identify MGI mouse gene symbols, which have been converted to date format by Excel, withdrawn, or aliased. It also contains functions for reversibly converting between HGNC symbols and valid R names.

This package provides smooth additive quantile regression models, fitted using the methods of Fasiolo et al. (2017). Differently from quantreg, the smoothing parameters are estimated automatically by marginal loss minimization, while the regression coefficients are estimated using either PIRLS or Newton algorithm. The learning rate is determined so that the Bayesian credible intervals of the estimated effects have approximately the correct coverage. The main function is qgam() which is similar to gam() in the mgcv package, but fits non-parametric quantile regression models.

This package implements generalized Deming regression, Theil-Sen regression and Passing-Bablock regression functions.

This package provides non-statistical utilities used by the software developed by the Statnet Project.

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.

This package provides functions for reading ontologies into R as lists and manipulating sets of ontological terms.

This package provides a collection of miscellaneous 3d plots, including isosurfaces.

Network Common Data Form (netCDF) files are widely used for scientific data. Library-level access in R is provided through packages RNetCDF and ncdf4. The package ncdfCF is built on top of RNetCDF and makes the data and its attributes available as a set of R6 classes that are informed by the Climate and Forecasting Metadata Conventions. Access to the data uses standard R subsetting operators and common function forms.

UpSet plots are an improvement over Venn Diagram for set overlap visualizations. Striving to bring the best of the UpSetR and ggplot2, this package offers a way to create complex overlap visualisations, using simple and familiar tools.

This package provides simple utility functions to read from and write to the system clipboards.

This package provides support for all calendars as specified in the Climate and Forecast (CF) Metadata Conventions for climate and forecasting data. The CF Metadata Conventions is widely used for distributing files with climate observations or projections, including the Coupled Model Intercomparison Project (CMIP) data used by climate change scientists and the Intergovernmental Panel on Climate Change (IPCC). This package specifically allows the user to work with any of the CF-compliant calendars (many of which are not compliant with POSIXt). The CF time coordinate is formally defined in the CF Metadata Conventions document.

Apache Arrow is a cross-language development platform for in-memory data. It specifies a standardized language-independent columnar memory format for flat and hierarchical data, organized for efficient analytic operations on modern hardware. This package provides an R interface to the Arrow C++ library.

This package allows the user to specify debug messages as special string constants, and control debugging of packages via environment variables.

This package provides the datasets to support the Fish Stock Assessment (FSA) package.