qrNLMM-package: Package for Quantile Regression for Linear Mixed-Effects...
In qrNLMM: Quantile Regression for Nonlinear Mixed-Effects Models
qrNLMM-package R Documentation
Package for Quantile Regression for Linear Mixed-Effects Model
Description
This package contains a principal function that performs a quantile regression for a Nonlinear Mixed-Effects Model using the Stochastic-Approximation of the EM Algorithm (SAEM) for an unique or a set of quantiles.
Exploiting the nice hierarchical representation of the ALD, our classical approach follows the Stochastic Approximation of the EM(SAEM) algorithm for deriving exact maximum likelihood estimates of the fixed-effects and variance components.
Details
Package: qrNLMM
Type: Package
Version: 1.0
Date: 2015-01-30
License: What license is it under?
Author(s)
Christian E. Galarza <chedgala@espol.edu.ec> and
Victor H. Lachos <hlachos@ime.unicamp.br>
Maintainer: Christian E. Galarza <chedgala@espol.edu.ec>
References
Galarza, C.E., Castro, L.M., Louzada, F. & Lachos, V. (2020) Quantile regression for nonlinear mixed effects models: a likelihood based perspective. Stat Papers 61, 1281-1307.
doi: 10.1007/s00362-018-0988-y
Yu, K. & Moyeed, R. (2001). Bayesian quantile regression. Statistics & Probability Letters, 54(4), 437-447.
Yu, K., & Zhang, J. (2005). A three-parameter asymmetric Laplace distribution and its extension. Communications in Statistics-Theory and Methods, 34(9-10), 1867-1879.
See Also
Soybean, HIV, QRNLMM,
lqr , group.plots
Examples
#See examples for the QRNLMM function linked above.
qrNLMM documentation built on Aug. 18, 2022, 5:05 p.m.
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| qrNLMM-package | R Documentation |
Package for Quantile Regression for Linear Mixed-Effects Model
Description
This package contains a principal function that performs a quantile regression for a Nonlinear Mixed-Effects Model using the Stochastic-Approximation of the EM Algorithm (SAEM) for an unique or a set of quantiles.
Exploiting the nice hierarchical representation of the ALD, our classical approach follows the Stochastic Approximation of the EM(SAEM) algorithm for deriving exact maximum likelihood estimates of the fixed-effects and variance components.
Details
| Package: | qrNLMM |
| Type: | Package |
| Version: | 1.0 |
| Date: | 2015-01-30 |
| License: | What license is it under? |
Author(s)
Christian E. Galarza <chedgala@espol.edu.ec> and Victor H. Lachos <hlachos@ime.unicamp.br>
Maintainer: Christian E. Galarza <chedgala@espol.edu.ec>
References
Galarza, C.E., Castro, L.M., Louzada, F. & Lachos, V. (2020) Quantile regression for nonlinear mixed effects models: a likelihood based perspective. Stat Papers 61, 1281-1307. doi: 10.1007/s00362-018-0988-y
Yu, K. & Moyeed, R. (2001). Bayesian quantile regression. Statistics & Probability Letters, 54(4), 437-447.
Yu, K., & Zhang, J. (2005). A three-parameter asymmetric Laplace distribution and its extension. Communications in Statistics-Theory and Methods, 34(9-10), 1867-1879.
See Also
Soybean, HIV, QRNLMM,
lqr , group.plots
Examples
#See examples for the QRNLMM function linked above.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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