mixAK (version 2.2)

GLMM_MCMCifit: 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, lalpha, 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

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

lalpha

see output element lalpha 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 subjects (grouped observations) 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)
• ibMat2
  matrix with alternative initial values of random effects
• iEranefVec
  vector with estimated means of random effects
• iSDranefVec
  vector with estimated standard deviations of random effects
• iSEranefVec
  vector with standard errors of estimated means of random effects
• ialpha
  vector with initial values of alpha's (including fixed intercepts)
• ialpha2
  vector with alternative initial values of alpha's (including fixed intercepts)
• iSEalpha
  vector with standard errors of estimated values of fixed effects

See Also

GLMM_MCMC.