rControl {glmmPen} | R Documentation |
Control of Latent Factor Model Number Estimation
Constructs the control structure for the estimation of the
number of latent factors (r) for use within the glmmPen_FA
and
glmm_FA
estimation procedures.
Description
Control of Latent Factor Model Number Estimation
Constructs the control structure for the estimation of the
number of latent factors (r) for use within the glmmPen_FA
and
glmm_FA
estimation procedures.
Usage
rControl(
r = NULL,
r_max = NULL,
r_est_method = "GR",
size = 25,
sample = FALSE
)
Arguments
r |
positive integer specifying number of latent common factors to assume
in the model. If |
r_max |
positive integer specifying maximum number of latent factors to consider.
If |
r_est_method |
character string indicating method used to estimate number
of latent factors |
size |
positive integer specifying the total number of pseudo random
effect estimates to use in the estimation procedure for the number of latent factors
r, which is restricted to be no less than 25. If this |
sample |
logical value indicating if the total number of pseudo random effect
estimates to use in the estimation procedure for the number of latent common factors r
should be larger than the number of unique groups in the data, where the number
of pseudo estimates are increased to the value of |
Details
Estimation of r
procedure: For each level of the group variable separately,
we identify the observations within that group and
fit a regular penalized generalized linear model where the penalty value is the
minimum fixed effect penalty. These group-specific estimates, which we label as 'pseudo random effects',
are placed into a matrix G
(rows = number of levels of the grouping variable, columns = number of random effect covariates),
and this pseudo random effects matrix is treated as the observed outcome matrix used in
the "GR", "ER", and "BN" estimation procedures described above in the description of r_est_method
.