mcnr_step: Newton-Raphson step for the MCMCML algorithm
In samuel-watson/glmmr: Design and analysis for generalised linear mixed models in R
mcnr_step R Documentation
Newton-Raphson step for the MCMCML algorithm
Description
Newton-Raphson step for the MCMCML algorithm
Usage
mcnr_step(y, X, Z, beta, u, family, link)
Arguments
y
Vector of observations
X
Matrix X of the GLMM
Z
Matrix Z of the GLMM
beta
A vector specifying the current values of the mean function parameters
u
Matrix of samples of the random effects. Each column is a sample.
family
Character specifying the family
link
Character specifying the link function
Value
A vector specifying the Newton-Raphson step for the parameters
samuel-watson/glmmr documentation built on July 27, 2022, 10:30 p.m.
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| mcnr_step | R Documentation |
Newton-Raphson step for the MCMCML algorithm
Description
Newton-Raphson step for the MCMCML algorithm
Usage
mcnr_step(y, X, Z, beta, u, family, link)
Arguments
y |
Vector of observations |
X |
Matrix X of the GLMM |
Z |
Matrix Z of the GLMM |
beta |
A vector specifying the current values of the mean function parameters |
u |
Matrix of samples of the random effects. Each column is a sample. |
family |
Character specifying the family |
link |
Character specifying the link function |
Value
A vector specifying the Newton-Raphson step for the parameters
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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