The strip function deletes components of R model outputs that are useless for specific purposes, such as predict[ing], print[ing], summary[izing], etc.

Efficient regression analysis under general two-phase sampling, where Phase I includes error-prone data and Phase II contains validated data on a subset.

Function library for processing collective movement data (e.g. fish schools, ungulate herds, baboon troops) collected from GPS trackers or computer vision tracking software.

Density, distribution function, quantile function and random generation for the sum of independent non-identical binomial distribution with parameters \codesize and \codeprob.

Return the first four moments, estimation of parameters and sample of the TSMSN distributions (Skew Normal, Skew t, Skew Slash or Skew Contaminated Normal).

Assortativity coefficients, centrality measures, and clustering coefficients for weighted and directed networks. Rewiring unweighted networks with given assortativity coefficients. Generating general preferential attachment networks.

Finds drugs and drug combinations that are predicted to reverse or mimic gene expression signatures. These drugs might reverse diseases or mimic healthy lifestyles.

This package uses an innovative network-based approach that will enhance our ability to determine the identities of significant ions detected by LC-MS.

Quantitative and differential analysis of epigenomic and transcriptomic time course sequencing data, clustering analysis and visualization of the temporal patterns of time course data.

This package provides extra utility functions to perform common tasks in the analysis of omics data, leveraging and enhancing features provided by Bioconductor packages.

This package provides tools to execute arbitrary R or C functions some time after the current time, after the R execution stack has emptied.

This package provides a package for quantifying, profiling and removing cell free mRNA contamination (the "soup") from droplet based single cell RNA-seq experiments.

This package provides a collection of helper functions designed to help you to better understand object oriented programming in R, particularly using S3.

This package provides functions and vignettes to update data sets in Ecdat and to create, manipulate, plot, and analyze those and similar data sets.

This package provides a collection of ggplot2 color palettes inspired by plots in scientific journals, data visualization libraries, science fiction movies, and TV shows.

The main type exported by this library, BitVec, is a packed, growable bit-vector. Its API mirrors that of Vec where reasonable.

Robocut is a simple graphical program that allows you to cut graphics with Graphtec and Sihouette plotting cutters using an SVG file as its input.

Oj is a JSON parser and generator for Ruby, where the encoding and decoding of JSON is implemented as a C extension to Ruby.

The RSP markup language provides a powerful markup for controlling the content and output of LaTeX, HTML, Markdown, AsciiDoc, Sweave and knitr documents (and more), e.g. Today's date is <%=Sys.Date()%>. Contrary to many other literate programming languages, with RSP it is straightforward to loop over mixtures of code and text sections, e.g. in month-by-month summaries. RSP has also several preprocessing directives for incorporating static and dynamic contents of external files (local or online) among other things. RSP is ideal for self-contained scientific reports and R package vignettes.

Calculates tide heights based on tide station harmonics. It includes the harmonics data for 637 US stations. The harmonics data was converted from <https://github.com/poissonconsulting/rtide/blob/main/data-raw/harmonics-dwf-20151227-free.tar.bz2>, NOAA web site data processed by David Flater for XTide'. The code to calculate tide heights from the harmonics is based on XTide'.

Interface to easily access data via the United States Department of Agriculture (USDA)'s Agricultural Resource Management Survey (ARMS) Data API <https://www.ers.usda.gov/developer/data-apis/arms-data-api/>. The downloaded data can be saved for later off-line use. Also provide relevant information and metadata for each of the input variables needed for sending the data inquery.

MCFS-ID (Monte Carlo Feature Selection and Interdependency Discovery) is a Monte Carlo method-based tool for feature selection. It also allows for the discovery of interdependencies between the relevant features. MCFS-ID is particularly suitable for the analysis of high-dimensional, small n large p transactional and biological data. M. Draminski, J. Koronacki (2018) <doi:10.18637/jss.v085.i12>.

Represents high-dimensional data as tables of features, samples and measurements, and a design list for tracking the meaning of individual variables. Using this format, filtering, normalization, and other transformations of a dataset can be carried out in a flexible manner. romic takes advantage of these transformations to create interactive shiny apps for exploratory data analysis such as an interactive heatmap.

Routines to select and visualize the maxima for a given strict partial order. This especially includes the computation of the Pareto frontier, also known as (Top-k) Skyline operator (see Börzsönyi, et al. (2001) <doi:10.1109/ICDE.2001.914855>), and some generalizations known as database preferences (see Kieà ling (2002) <doi:10.1016/B978-155860869-6/50035-4>).