This package provides an easy and simple way to read, write and display bitmap images stored in the TIFF format. It can read and write both files and in-memory raw vectors.

This package provides tools to create a lightweight Shiny wrapper for the css-loaders created by Luke Hass https://github.com/lukehaas/css-loaders. Wrapping a Shiny output will automatically show a loader when the output is (re)calculating.

Multiple imputation using Fully Conditional Specification (FCS) implemented by the MICE algorithm as described in http://doi.org/10.18637/jss.v045.i03. Each variable has its own imputation model. Built-in imputation models are provided for continuous data (predictive mean matching, normal), binary data (logistic regression), unordered categorical data (polytomous logistic regression) and ordered categorical data (proportional odds). MICE can also impute continuous two-level data (normal model, pan, second-level variables). Passive imputation can be used to maintain consistency between variables. Various diagnostic plots are available to inspect the quality of the imputations.

This package extends sparse matrix and vector classes from the Matrix package by providing:

1. Methods and operators that work natively on CSR formats (compressed sparse row, a.k.a. RsparseMatrix) such as slicing/sub-setting, assignment, rbind(), mathematical operators for CSR and COO such as addition or sqrt(), and methods such as diag();

2. Multi-threaded matrix multiplication and cross-product for many <sparse, dense> types, including the float32 type from float;

3. Coercion methods between pairs of classes which are not present in Matrix, such as from dgCMatrix to ngRMatrix, as well as convenience conversion functions;

4. Utility functions for sparse matrices such as sorting the indices or removing zero-valued entries;

5. Fast transposes that work by outputting in the opposite storage format;

6. Faster replacements for many Matrix methods for all sparse types, such as slicing and elementwise multiplication.

7. Convenience functions for sparse objects, such as mapSparse or a shorter show method.

The Rsolnp package implements a general non-linear augmented Lagrange multiplier method solver, a sequential quadratic programming (SQP) based solver).

This is a package for simplified document database access and manipulation, providing a common API across supported NoSQL databases Elasticsearch, CouchDB, MongoDB as well as SQLite/JSON1, PostgreSQL, and DuckDB.

Constructs confidence intervals on the probability of success in a binomial experiment via several parameterizations

The main aim of the pander R package is to provide a minimal and easy tool for rendering R objects into Pandoc's markdown. The package is also capable of exporting/converting complex Pandoc documents (reports) in various ways.

This package contains functions for non-parametric survival analysis of exact and interval-censored observations.

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

This package provides a simple method for representing a visual scene as it may be seen by an animal with less acute vision.

Single cell RNA sequencing datasets can be large, consisting of matrices that contain expression data for several thousand features across several thousand cells. This package is designed to easily install, manage, and learn about various single-cell datasets, provided Seurat objects and distributed as independent packages.

The aim of httr is to provide a wrapper for RCurl customised to the demands of modern web APIs. It provides useful tools for working with HTTP organised by HTTP verbs (GET(), POST(), etc). Configuration functions make it easy to control additional request components.

This package provides statistical procedures for calculating population-mean cosinor, non-stationary cosinor, estimation of best-fitting period, tests of population rhythm differences and more.

This package implements the regularized Gaussian maximum likelihood estimation of the inverse of a covariance matrix. It uses Newton's method and coordinate descent to solve the regularized inverse covariance matrix estimation problem.

This package provides the "enrich" method to enrich list-like R objects with new, relevant components. The current version has methods for enriching objects of class family, link-glm, lm, glm and betareg. The resulting objects preserve their class, so all methods associated with them still apply. The package also provides the enriched_glm function that has the same interface as glm but results in objects of class enriched_glm. In addition to the usual components in a glm object, enriched_glm objects carry an object-specific simulate method and functions to compute the scores, the observed and expected information matrix, the first-order bias, as well as model densities, probabilities, and quantiles at arbitrary parameter values. The package can also be used to produce customizable source code templates for the structured implementation of methods to compute new components and enrich arbitrary objects.

This package allows the estimation of hierarchical F-statistics from haploid or diploid genetic data with any numbers of levels in the hierarchy, following the algorithm of Yang (Evolution, 1998, 52(4):950-956). Functions are also given to test via randomisations the significance of each F and variance components, using the likelihood-ratio statistics G.

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.

This package provides infrastructure to accurately measure and compare the execution time of R expressions.

This package OrgMassSpecR is an extension of the R statistical computing language. It contains functions to assist with organic or biological mass spectrometry data analysis. Mass spectral libraries are available as companion packages.

This package provides statistical methods especially developed to analyze anthropometric data. These methods are aimed at providing effective solutions to some commons problems related to Ergonomics and Anthropometry. They are based on clustering, the statistical concept of data depth, statistical shape analysis and archetypal analysis.

This package allows you to render vector-based SVG images into high-quality custom-size bitmap arrays using the librsvg2 library. The resulting bitmap can be written to e.g. PNG, JPEG or WEBP format. In addition, the package can convert images directly to various formats such as PDF or PostScript.

This package provides some functions for sample classification in microarrays.

Tools to clean and process text. Tools are geared at checking for substrings that are not optimal for analysis and replacing or removing them (normalizing) with more analysis friendly substrings (see Sproat, Black, Chen, Kumar, Ostendorf, & Richards (2001) doi:10.1006/csla.2001.0169) or extracting them into new variables. For example, emoticons are often used in text but not always easily handled by analysis algorithms. The replace_emoticon() function replaces emoticons with word equivalents.