| mcd_estimation {jmcm} | R Documentation | 
Fit Joint Mean-Covariance Models based on MCD
Description
Fit joint mean-covariance models based on MCD.
Usage
mcd_estimation(m, Y, X, Z, W, start, mean, trace = FALSE, profile = TRUE,
  errormsg = FALSE, covonly = FALSE, optim_method = "default")
Arguments
m | 
 an integer vector of numbers of measurements for subject.  | 
Y | 
 a vector of responses for all subjects.  | 
X | 
 model matrix for the mean structure model.  | 
Z | 
 model matrix for the diagonal matrix.  | 
W | 
 model matrix for the lower triangular matrix.  | 
start | 
 starting values for the parameters in the model.  | 
mean | 
 when covonly is true, it is used as the given mean.  | 
trace | 
 the values of the objective function and the parameters are printed for all the trace'th iterations.  | 
profile | 
 whether parameters should be estimated sequentially using the idea of profile likelihood or not.  | 
errormsg | 
 whether or not the error message should be print.  | 
covonly | 
 estimate the covariance structure only, and use given mean.  | 
optim_method | 
 optimization method, choose "default" or "BFGS"(vmmin in R).  | 
See Also
acd_estimation for joint mean covariance model fitting
based on ACD, hpc_estimation for joint mean covariance
model fitting based on HPC.