integratere {brmsmargins} R Documentation

## Integrate over Random Effects

### Description

Used to conduct Monte Carlo integration over Gaussian random effects. Not intended to be called directly by most users.

### Usage

integratere(d, sd, L, k, yhat, backtrans)

integratereR(d, sd, L, k, yhat, backtrans)


### Arguments

 d A list with model matrices for each random effect block. sd A list with standard deviation matrices for each random effect block where rows are different posterior draws. L A list with matrices for each random effect block containing the parts of the L matrix, the Cholesky decomposition of the random effect correlation matrix. k An integer, the number of samples for Monte Carlo integration. yhat A matrix of the fixed effects predictions backtrans An integer, indicating the type of back transformation. 0 indicates inverse logit (e.g., for logistic regression). 1 indicates exponential (e.g., for poisson or negative binomial regression or if outcome was natural log transformed). 2 indicates square (e.g., if outcome was square root transformed). 3 indicates inverse (e.g., if outcome was inverse transformed such as Gamma regression) Any other integer results in no transformation. -9 is recommended as the option for no transformation as any future transformations supported will be other, positive integers.

### Value

A numeric matrix with the Monte Carlo integral calculated.

### Functions

• integratereR: Pure R implementation of integratere

### Examples

integratere(
d = list(matrix(1, 1, 1)),
sd = list(matrix(1, 2, 1)),
L = list(matrix(1, 2, 1)),
k = 10L,
yhat = matrix(0, 2, 1),
backtrans = 0L)


[Package brmsmargins version 0.2.0 Index]