update_lmm_variance {catalytic} | R Documentation |
Calculates the log-likelihood for linear mixed models (LMMs) by combining observed and synthetic log-likelihoods based on the variance parameters.
Description
This function evaluates the log-likelihood of observed and synthetic data, using residual and random-effect variance terms to determine the fit of variance parameters in the mixed model context.
Usage
update_lmm_variance(
residual_variance,
random_effect_variance,
obs_z_eigenvalues,
syn_z_eigenvalues,
obs_adjusted_residuals,
syn_adjusted_residuals,
tau
)
Arguments
residual_variance |
Numeric, the variance associated with the residual errors. |
random_effect_variance |
Numeric, the variance associated with random effects. |
obs_z_eigenvalues |
Vector, eigenvalues of the observed Z matrix of data. |
syn_z_eigenvalues |
Vector, eigenvalues of the synthetic Z matrix of data. |
obs_adjusted_residuals |
Vector, adjusted residuals of observed data. |
syn_adjusted_residuals |
Vector, adjusted residuals of synthetic data. |
tau |
Numeric, weight factor for the synthetic data. |
Value
The sum of observed and synthetic log-likelihoods.
[Package catalytic version 0.1.0 Index]