GLMM_MCMCifit {mixAK}R Documentation

Initial (RE)ML fits for the GLMM_MCMC function

Description

This is a help function for GLMM_MCMC function. Besides initial (RE)ML fits, the function created variables derived from the design matrices.

THIS FUNCTION IS NOT TO BE CALLED BY ORDINARY USERS.

Usage

GLMM_MCMCifit(do.init, na.complete,
    y, dist, id, time, x, z, random.intercept,
    xempty, zempty, Rc, Rd, p, p_fi, q, q_ri, lbeta, dimb)

Arguments

do.init logical value indicating whether initial (RE)ML fits should be done
na.complete logical value. If TRUE then the function removes rows containing NA's from y, id, x, z whenever there is at least one missing value for arbitrary response. If FALSE then the missing values are removed response by response, i.e., different response variables may have different numbers of observations.
y see output element y of GLMM_MCMCdata function
dist see argumentdist of GLMM_MCMC function
id see output element id of GLMM_MCMCdata function
time see argument time of GLMM_longitClust
x see output element x of GLMM_MCMCdata function
z see output element z of GLMM_MCMCdata function
random.intercept see output element random.intercept of GLMM_MCMCdata function
xempty see output element xempty of GLMM_MCMCdata function
zempty see output element zempty of GLMM_MCMCdata function
Rc see output element Rc of GLMM_MCMCdata function
Rd see output element Rd of GLMM_MCMCdata function
p see output element p of GLMM_MCMCdata function
p_fi see output element p_fi of GLMM_MCMCdata function
q see output element q of GLMM_MCMCdata function
q_ri see output element q_ri of GLMM_MCMCdata function
lbeta see output element lbeta of GLMM_MCMCdata function
dimb see output element dimb of GLMM_MCMCdata function

Value

A list with the following components (some of them not included if do.init is FALSE):

Y a list of length R with observations really used in fitting process (after removal of missing values)
ID a list of length R with id's corresponding to Y
time a vector time upon removal of missing values
x a list resulting from the original argument x after removal of observations with some missing information additionaly, intercept column is added if fixed intercept included in the model
z a list resulting from the original argument z after removal of observations with some missing information additionaly, intercept column is added if random intercept included in the model
I number of clusters in the original data (before removing NA's)
n a list of length R, each component is a vector or length I (may contain zeros if some cluster disappears for particular response due to NA's)
Cn vectorized n
sumCn sum(Cn) = total number of observations
Cy_c vector with continuous response to be passed to C++, equal to 0 if there is no continuous response
Cy_d vector with discrete response to be passed to C++, equal to 0 if there is no discrete response
CX vector containing X matrices (without ones for possible intercept) to be passed to C++, equal to 0 if there are no X matrices
CZ vector containing Z matrices (without ones for possible intercept) to be passed to C++, equal to 0 if there are no Z matrices
iintcpt data.frame(Est, SE) with estimated intercepts and their SE, R rows, row equal to (0, 0) if there is no fixed intercept for particular response
ifixef a list of length R, each component is equal to 0 if there are no fixed effects for particular response, and is equal to data.frame(Est, SE) if there are fixed effects
isigma vector of length R, equal to 0 for discrete response, equal to estimated residual standard deviation for continuous response
iEranef a list of length R, each component is equal to 0 if there are no random effects for particular response, and is equal to data.frame(Est, SE) with estimated means of the random effects and their std. errors if there are random effects
iSDranef a list of length R, each component is equal to 0 if there are no random effects for particular response, and is equal to a vector with estimated standard deviations of the random effects if there are random effects
ib a list of length R, each component is equal to 0 if there are no random effects for particular response, and a matrix with EB estimates of random effects shifted by their estimated mean if there are random effects
is.intcpt logical vector of length R
is.fixef logical vector of length R
is.ranef logical vector of length R
is.sigma logical vector of length R
ibMat matrix with initial values of random effects (EB estimates from (RE)ML fits)
iEranefVec vector with estimated means of random effects
iSEranefVec vector with standard errors of estimated means of random effects
iSDranefVec vector with estimated standard deviations of random effects
ibeta vector with initial values of beta's (including fixed intercepts)

Author(s)

Arnošt Komárek arnost.komarek[AT]mff.cuni.cz

See Also

GLMM_MCMC.


[Package mixAK version 0.6 Index]