This package provides an implementation of scatter plots for plotting. a three dimensional point cloud.

This package provides functions for estimating tolerance limits (intervals) for various univariate distributions (binomial, Cauchy, discrete Pareto, exponential, two-parameter exponential, extreme value, hypergeometric, Laplace, logistic, negative binomial, negative hypergeometric, normal, Pareto, Poisson-Lindley, Poisson, uniform, and Zipf-Mandelbrot), Bayesian normal tolerance limits, multivariate normal tolerance regions, nonparametric tolerance intervals, tolerance bands for regression settings (linear regression, nonlinear regression, nonparametric regression, and multivariate regression), and analysis of variance tolerance intervals. Visualizations are also available for most of these settings.

This package provides an implementation of cumulative link (mixed) models also known as ordered regression models, proportional odds models, proportional hazards models for grouped survival times and ordered models. Estimation is via maximum likelihood and mixed models are fitted with the Laplace approximation and adaptive Gauss-Hermite quadrature.

The wordspace package turns R into an interactive laboratory for empirical research on distributional semantic models (DSM). It consists of a small set of carefully designed functions, most of which

• encapsulate non-trivial R operations in a user-friendly manner or

• provide efficient and memory-lean C implementations of key operations.

Bivariate data interpolation on regular and irregular grids, either linear or using splines are the main part of this package. It is intended to provide replacement functions for the ACM licensed akima::interp and tripack::tri.mesh functions.

This package provides pre-fit and post-fit methods for detecting separation and infinite maximum likelihood estimates in generalized linear models with categorical responses. The pre-fit methods apply on binomial-response generalized liner models such as logit, probit and cloglog regression, and can be directly supplied as fitting methods to the glm() function. The post-fit methods apply to models with categorical responses, including binomial-response generalized linear models and multinomial-response models, such as baseline category logits and adjacent category logits models; for example, the models implemented in the brglm2 package. The post-fit methods successively refit the model with increasing number of iteratively reweighted least squares iterations, and monitor the ratio of the estimated standard error for each parameter to what it has been in the first iteration.

This package provides a set of predicates and assertions for checking the properties of code. This is mainly for use by other package developers who want to include run-time testing features in their own packages.

This package provides code analysis tools for R to check R code for possible problems.

This package contains linear and nonlinear regression methods based on partial least squares and penalization techniques. Model parameters are selected via cross-validation, and confidence intervals ans tests for the regression coefficients can be conducted via jackknifing.

This package provides methods and algorithms for discrete optimization, e.g. knapsack and subset sum procedures, derivative-free Nelder-Mead and Hooke-Jeeves minimization, and some (evolutionary) global optimization functions.

This package provides a color picker that can be used as an input in Shiny apps or Rmarkdown documents. The color picker supports alpha opacity, custom color palettes, and many more options. A plot color helper tool is available as an RStudio Addin, which helps you pick colors to use in your plots. A more generic color picker RStudio Addin is also provided to let you select colors to use in your R code.

This package provides tools to create some specific Space-Filling Design (SFD) and to test their quality.

This package extends mlr3 with filter methods for feature selection. Besides standalone filter methods built-in methods of any machine-learning algorithm are supported. Partial scoring of multivariate filter methods is supported.

This package provides a more scalable alternative to Venn and Euler diagrams for visualizing intersecting sets. Create visualizations of intersecting sets using a novel matrix design, along with visualizations of several common set, element and attribute related tasks.

Tools that can be used to reshape and restructure text data.

This package provides a DBI interface to MySQL / MariaDB. The RMySQL package contains an old implementation based on legacy code from S-PLUS which is being phased out. A modern MySQL client based on Rcpp is available from the RMariaDB package.

This package provides a set of tools to help explain which variables are most important in a random forests. Various variable importance measures are calculated and visualized in different settings in order to get an idea on how their importance changes depending on our criteria (Hemant Ishwaran and Udaya B. Kogalur and Eiran Z. Gorodeski and Andy J. Minn and Michael S. Lauer (2010) <doi:10.1198/jasa.2009.tm08622>, Leo Breiman (2001) <doi:10.1023/A:1010933404324>).

This package provides fundamental physical constants (quantity, value, uncertainty, unit) for SI and non-SI units, plus unit conversions based on the data from NIST, USA.

This package provides support for the foreach looping construct. foreach is an idiom that allows for iterating over elements in a collection, without the use of an explicit loop counter. This package in particular is intended to be used for its return value, rather than for its side effects. In that sense, it is similar to the standard lapply function, but doesn't require the evaluation of a function. Using foreach without side effects also facilitates executing the loop in parallel.

OOMPA offers R packages for gene expression and proteomics analysis. OOMPA uses S4 classes to construct object-oriented tools with a consistent user interface. All higher level analysis tools in OOMPA are compatible with the eSet classes defined in BioConductor. The lower level processing tools offer an alternative to parts of BioConductor, but can also be used to enhance existing BioConductor packages.

This package provides an R interface to the GNU Linear Programming Kit, software for solving large-scale linear programming (LP), mixed integer linear programming (MILP) and other related problems.

This package provides high performance container data types such as queues, stacks, deques, dicts and ordered dicts.

This package provides a header only, C++11 interface to R's C interface. Compared to other approaches cpp11 strives to be safe against long jumps from the C API as well as C++ exceptions, conform to normal R function semantics and supports interaction with ALTREP vectors.

The ACE file format is used in genomics to store contigs from sequencing machines. This tools converts it into FASTQ format. Both formats contain the sequence characters and their corresponding quality information. Unlike the FASTQ file, the ACE file stores the quality values numerically. The conversion algorithm uses the standard Sanger formula. The package facilitates insertion into pipelines, and content inspection.