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Magic Enum offers static reflection of enums, with conversions to and from strings, iteration and related functionality.
GNU Cppi processes C source code files to properly indent the preprocessor directives to reflect their nesting. It also performs other standardizations, such as correcting the number of spaces between directives and the text following them.
This a package containing diverse spatial datasets for demonstrating, benchmarking and teaching spatial data analysis. It includes R data of class sf, Spatial, and nb. It also contains data stored in a range of file formats including GeoJSON, ESRI Shapefile and GeoPackage. Some of the datasets are designed to illustrate specific analysis techniques. cycle_hire() and cycle_hire_osm(), for example, are designed to illustrate point pattern analysis techniques.
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.
Kernel factory is an ensemble method where each base classifier (random forest) is fit on the kernel matrix of a subset of the training data.
Ggplot2 is an implementation of the grammar of graphics in R. It combines the advantages of both base and lattice graphics: conditioning and shared axes are handled automatically, and you can still build up a plot step by step from multiple data sources. It also implements a sophisticated multidimensional conditioning system and a consistent interface to map data to aesthetic attributes.
This package provides a mutation analysis tool that discovers cancer driver genes with frequent mutations in protein signalling sites such as post-translational modifications (phosphorylation, ubiquitination, etc). The Poisson generalized linear regression model identifies genes where cancer mutations in signalling sites are more frequent than expected from the sequence of the entire gene. Integration of mutations with signalling information helps find new driver genes and propose candidate mechanisms to known drivers.
This package uses the node library is-my-json-valid or ajv to validate JSON against a JSON schema. Drafts 04, 06 and 07 of JSON schema are supported.
The purpose of this package is to provide a lightweight and unified Future API for sequential and parallel processing of R expression via futures. This package implements sequential, multicore, multisession, and cluster futures. With these, R expressions can be evaluated on the local machine, in parallel a set of local machines, or distributed on a mix of local and remote machines. Extensions to this package implement additional backends for processing futures via compute cluster schedulers etc. Because of its unified API, there is no need to modify any code in order to switch from sequential on the local machine to, say, distributed processing on a remote compute cluster.
This package performs Bayesian calibration of computer models as per Kennedy and O'Hagan 2001. The package includes routines to find the hyperparameters and parameters; see the help page for stage1() for a worked example using the toy dataset. A tutorial is provided in the calex.Rnw vignette; and a suite of especially simple one dimensional examples appears in inst/doc/one.dim/.
This package provides functions for importing external vector images and drawing them as part of R plots. This package is different from the grImport package because, where that package imports PostScript format images, this package imports SVG format images. Furthermore, this package imports a specific subset of SVG, so external images must be preprocessed using a package like rsvg to produce SVG that this package can import. SVG features that are not supported by R graphics, such as gradient fills, can be imported and then exported via the gridSVG package.
This package implements list environments. List environments are environments that have list-like properties. For instance, the elements of a list environment are ordered and can be accessed and iterated over using index subsetting.
This is a supplement to the maps package providing the larger and/or higher-resolution databases.
This package lets you fit pedigree-based mixed-effects models.
This package provides easy-to-use and versatile functions to output R objects in HTML format.
This package provides functions for estimating marginal likelihoods, Bayes factors, posterior model probabilities, and normalizing constants in general, via different versions of bridge sampling.
This package provides a differential evolution (DE) stochastic algorithms for global optimization of problems with and without constraints. The aim is to curate a collection of its state-of-the-art variants that
do not sacrifice simplicity of design,
are essentially tuning-free, and
can be efficiently implemented directly in the R language.
This package provides various themes, palettes, and other functions that are used to customise ggplots to look like they were made in GraphPad Prism. The Prism-look is achieved with theme_prism() and scale_fill|colour_prism(), axes can be changed with custom guides like guide_prism_minor(), and significance indicators added with add_pvalue().
This package provides an interface to Amazon Web Services, including storage, database, and compute services, such as Simple Storage Service (S3), DynamoDB NoSQL database, and Lambda functions-as-a-service.
This package provides functions to calculate: moments, Pearson's kurtosis, Geary's kurtosis and skewness; it also includes tests related to them (Anscombe-Glynn, D'Agostino, Bonett-Seier).
This package provides the datasets to support the Fish Stock Assessment (FSA) package.
This package provides a replacement and extension of the optim function to call to several function minimization codes in R in a single statement. These methods handle smooth, possibly box constrained functions of several or many parameters. Note that the function optimr was prepared to simplify the incorporation of minimization codes going forward. This package also implements some utility codes and some extra solvers, including safeguarded Newton methods. Many methods previously separate are now included here.
Least Angle Regression ("LAR") is a model selection algorithm; a useful and less greedy version of traditional forward selection methods. A simple modification of the LAR algorithm implements Tibshirani's Lasso; the Lasso modification of LARS calculates the entire Lasso path of coefficients for a given problem at the cost of a single least squares fit. Another LARS modification efficiently implements epsilon Forward Stagewise linear regression.
This package provides a general toolkit for downloading, managing, analyzing, and presenting data from the U.S. Census, including SF1 (Decennial short-form), SF3 (Decennial long-form), and the American Community Survey (ACS). Confidence intervals provided with ACS data are converted to standard errors to be bundled with estimates in complex acs objects. The package provides new methods to conduct standard operations on acs objects and present/plot data in statistically appropriate ways.