Contains: 1) Facilities for working with grouped data: 'do' something to data stratified 'by' some variables. 2) LSmeans (least-squares means), general linear contrasts. 3) Miscellaneous other utilities.

The following several classes of frailty models using a penalized likelihood estimation on the hazard function but also a parametric estimation can be fit using this R package: 1) A shared frailty model (with gamma or log-normal frailty distribution) ...

For working with the 'DataRobot' predictive modeling platform's API <https://www.datarobot.com/>.

Performs analysis of variance testing procedures for univariate and multivariate functional data (Cuesta-Albertos and Febrero-Bande (2010) <doi:10.1007/s11749-010-0185-3>, Gorecki and Smaga (2015) <doi:10.1007/s00180-015-0555-0>, Gorecki and Smaga ...

We implement a common genotyping workflow with a standardized software interface. 'genotypeR' designs genotyping markers from vcf files, outputs markers for multiplexing suitability on various platforms (Sequenom and Illumina GoldenGate), and ...

This package contains functions to carry out processing of high throughput data analysis and detection of putative hits/mutants. Contents include a function for post-hoc quality control for removal of outlier sample sets, a median-based ...

Functions and datasets to support Valliant, Dever, and Kreuter, ``Practical Tools for Designing and Weighting Survey Samples'' (2nd edition, 2018). Contains functions for sample size calculation for survey samples using stratified or clustered one-, ...

Efficient calculation of pseudo-ranks and (pseudo)-rank based test statistics. In case of equal sample sizes, pseudo-ranks and mid-ranks are equal.

Contains functionalities for importing and managing downloaded genome annotation data from 'Ensembl' genome browser (European Bioinformatics Institute, <https://www.ensembl.org>) and from 'UCSC' genome browser (University of California, Santa Cruz, ...

Tools for performing phylogenetic comparative methods for datasets with with multiple observations per species (intraspecific variation or measurement error) and/or missing data. Performs ancestral state reconstruction and missing data imputation on ...

Functions that facilitate analysis of Sensory as well as Consumer data within a mixed effects model framework. The so-called mixed assessor models, that correct for the scaling effect are implemented.