Package: minque 2.0.0

minque: Various Linear Mixed Model Analyses

This package offers three important components: (1) to construct a use-defined linear mixed model, (2) to employ one of linear mixed model approaches: minimum norm quadratic unbiased estimation (MINQUE) (Rao, 1971) for variance component estimation and random effect prediction; and (3) to employ a jackknife resampling technique to conduct various statistical tests. In addition, this package provides the function for model or data evaluations.This R package offers fast computations for large data sets analyses for various irregular data structures.

Authors:Jixiang Wu

minque_2.0.0.tar.gz
minque_2.0.0.zip(r-4.5)minque_2.0.0.zip(r-4.4)minque_2.0.0.zip(r-4.3)
minque_2.0.0.tgz(r-4.4-any)minque_2.0.0.tgz(r-4.3-any)
minque_2.0.0.tar.gz(r-4.5-noble)minque_2.0.0.tar.gz(r-4.4-noble)
minque_2.0.0.tgz(r-4.4-emscripten)minque_2.0.0.tgz(r-4.3-emscripten)
minque.pdf |minque.html
minque/json (API)

# Install 'minque' in R:
install.packages('minque', repos = c('https://jacks306.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • brate - Cotton boll retention rate data
  • cot - Twenty four cotton genotypes with four agronomic traits
  • maize - Maize variety trial
  • ncii - NC design II F1 data

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

7 exports 0.71 score 0 dependencies 2 mentions 28 scripts 143 downloads

Last updated 5 years agofrom:3e3ea80a9e. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 10 2024
R-4.5-winOKSep 10 2024
R-4.5-linuxOKSep 10 2024
R-4.4-winOKSep 10 2024
R-4.4-macOKSep 10 2024
R-4.3-winOKSep 10 2024
R-4.3-macOKSep 10 2024

Exports:lmmlmm.checklmm.jacklmm.permlmm.simulmm.simu.jacklmm.simudata

Dependencies: