qrNLMM: Quantile Regression for Nonlinear Mixed-Effects Models

Share:

Quantile regression (QR) for Nonlinear Mixed-Effects Models via the asymmetric Laplace distribution (ALD). It uses the Stochastic Approximation of the EM (SAEM) algorithm for deriving exact maximum likelihood estimates and full inference results for the fixed-effects and variance components. It also provides graphical summaries for assessing the algorithm convergence and fitting results.

Author
Christian E. Galarza <cgalarza88@gmail.com> and Victor H. Lachos <hlachos@ime.unicamp.br>
Date of publication
2016-06-06 07:48:12
Maintainer
Christian E. Galarza <cgalarza88@gmail.com>
License
GPL (>= 2)
Version
1.3

View on CRAN

Man pages

group.plots
Plot function for grouped data
HIV
HIV viral load study
QRNLMM
Quantile Regression for Nonlinear Mixed-Effects Models
qrNLMM-package
Package for Quantile Regression for Linear Mixed-Effects...
Soybean
Growth of soybean plants

Files in this package

qrNLMM
qrNLMM/NAMESPACE
qrNLMM/data
qrNLMM/data/Soybean.txt.gz
qrNLMM/data/HIV.txt.gz
qrNLMM/R
qrNLMM/R/QSAEM_NLMM.R
qrNLMM/R/HelpfulFunctions.R
qrNLMM/R/QRNLMM.R
qrNLMM/MD5
qrNLMM/DESCRIPTION
qrNLMM/man
qrNLMM/man/HIV.Rd
qrNLMM/man/QRNLMM.Rd
qrNLMM/man/Soybean.Rd
qrNLMM/man/qrNLMM-package.Rd
qrNLMM/man/group.plots.Rd