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.
GLMM_MCMCifit(do.init, na.complete,
y, dist, id, time, x, z, random.intercept,
xempty, zempty, Rc, Rd, p, p_fi, q, q_ri, lalpha, dimb)
A list with the following components (some of them not included if
do.init
is FALSE
):
a list of length R with observations really used in fitting process (after removal of missing values)
a list of length R with id's corresponding to Y
a vector time
upon removal of missing values
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
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
number of subjects (grouped observations) in the original data (before removing NA's)
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)
vectorized n
sum(Cn) = total number of observations
vector with continuous response to be passed to C++, equal to 0 if there is no continuous response
vector with discrete response to be passed to C++, equal to 0 if there is no discrete response
vector containing X matrices (without ones for possible intercept) to be passed to C++, equal to 0 if there are no X matrices
vector containing Z matrices (without ones for possible intercept) to be passed to C++, equal to 0 if there are no Z matrices
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
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
vector of length R, equal to 0 for discrete response, equal to estimated residual standard deviation for continuous response
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
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
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
logical vector of length R
logical vector of length R
logical vector of length R
logical vector of length R
matrix with initial values of random effects (EB estimates from (RE)ML fits)
matrix with alternative initial values of random effects
vector with estimated means of random effects
vector with estimated standard deviations of random effects
vector with standard errors of estimated means of random effects
vector with initial values of alpha's (including fixed intercepts)
vector with alternative initial values of alpha's (including fixed intercepts)
vector with standard errors of estimated values of fixed effects
logical value indicating whether initial (RE)ML fits should be done
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.
see output element y
of GLMM_MCMCdata
function
see argumentdist
of GLMM_MCMC
function
see output element id
of GLMM_MCMCdata
function
see argument time
of GLMM_longitClust
see output element x
of GLMM_MCMCdata
function
see output element z
of GLMM_MCMCdata
function
see output element random.intercept
of GLMM_MCMCdata
function
see output element xempty
of GLMM_MCMCdata
function
see output element zempty
of GLMM_MCMCdata
function
see output element Rc
of GLMM_MCMCdata
function
see output element Rd
of GLMM_MCMCdata
function
see output element p
of GLMM_MCMCdata
function
see output element p_fi
of GLMM_MCMCdata
function
see output element q
of GLMM_MCMCdata
function
see output element q_ri
of GLMM_MCMCdata
function
see output element lalpha
of GLMM_MCMCdata
function
see output element dimb
of GLMM_MCMCdata
function
Arnošt Komárek arnost.komarek@mff.cuni.cz
GLMM_MCMC
.