Package: lqmm 1.5.8
Marco Geraci
lqmm: Linear Quantile Mixed Models
Functions to fit quantile regression models for hierarchical data (2-level nested designs) as described in Geraci and Bottai (2014, Statistics and Computing) <doi:10.1007/s11222-013-9381-9>. A vignette is given in Geraci (2014, Journal of Statistical Software) <doi:10.18637/jss.v057.i13> and included in the package documents. The packages also provides functions to fit quantile models for independent data and for count responses.
Authors:
lqmm_1.5.8.tar.gz
lqmm_1.5.8.tar.gz(r-4.5-noble)lqmm_1.5.8.tar.gz(r-4.4-noble)
lqmm_1.5.8.tgz(r-4.4-emscripten)lqmm_1.5.8.tgz(r-4.3-emscripten)
lqmm.pdf |lqmm.html✨
lqmm/json (API)
NEWS
| # Install 'lqmm' in R: |
| install.packages('lqmm', repos = 'https://cloud.r-project.org') |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:1e67c5514e. Checks:3 OK. Indexed: no.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 29 2025 |
| R-4.5-linux-x86_64 | OK | Mar 29 2025 |
| R-4.4-linux-x86_64 | OK | Mar 29 2025 |
Exports:addnoiseallVarsRecasOneFormulabandwidth.rqbootboot.lqmboot.lqmmC_gradientShC_gradientSiC_ll_hcoef.lqmcoef.lqm.countscoef.lqmmcovHandlingcreateLaguerredalerrorHandlingextractAllextractBootextractBoot.boot.lqmmF.lqmgauss.quadgauss.quad.probgradientSiinvTfuninvvarALis.positive.definitelogLik.lqmlogLik.lqmmloglik.sloglik.tloglikilqmlqm.countslqm.fit.gslqmControllqmmlqmm.fit.dflqmm.fit.gslqmmControlmake.positive.definitemeanALmleALpalpermutationspredict.lqmpredict.lqm.countspredict.lqmmpredintpredint.lqmmprint.lqmprint.lqm.countsprint.lqmmprint.summary.lqmprint.summary.lqmmqalquadralranefranef.lqmmresiduals.lqmresiduals.lqm.countsresiduals.lqmmscore.alsummary.boot.lqmsummary.boot.lqmmsummary.lqmsummary.lqmmswitch_checkTfuntheta.z.dimvarALVarCorrVarCorr.lqmm
Dependencies:latticenlmeSparseGrid
Citation
To cite package ‘lqmm’ in publications use:
Geraci M (2014). Linear Quantile Mixed Models: The lqmm Package for Laplace Quantile Regression. Journal of Statistical Software, 57(13), 1-29.
Geraci M and Bottai M (2014). Linear quantile mixed models. Statistics and Computing 24(3), 461-479.
A BibTeX entry for LaTeX users is toBibtex(citation('lqmm'))
Corresponding BibTeX entries:
@Article{,
title = {Linear Quantile Mixed Models: The {lqmm} Package for
Laplace Quantile Regression},
author = {Marco Geraci},
journal = {Journal of Statistical Software},
year = {2014},
volume = {57},
number = {13},
pages = {1--29},
doi = {10.18637/jss.v057.i13},
}
@Article{,
author = {Marco Geraci and Matteo Bottai},
title = {Linear quantile mixed models},
journal = {Statistics and Computing},
volume = {24},
number = {3},
pages = {461--479},
year = {2014},
doi = {10.1007/s11222-013-9381-9},
}
