Arguments
Yp
Matrix (observations by alternatives) of outcome proportions.
Values must be between 0 and 1. Missing data (NA values) are
not allowed.
Xarray
Array of regressors. dim(Xarray) = c(observations, parameters, alternatives).
xvec
Matrix (parameters by alternatives) that represents the model structure.
It has a 1 for an estimated parameter, an integer greater than 1 for an
estimated parameter constrained equal to another estimated parameter (all
parameters constrained to be equal to one another have the same integer
value in xvec) and a 0 otherwize.
jacstack
Array of regressors used to facilitate computing the gradient and the
hessian matrix.
dim(jacstack) = c(observations, unique parameters, alternatives).
start
A list of starting values of three kinds of parameters:
start$beta, the values for the regression coefficients; start$Omega, the
values for the variance-covariance matrix; start$df, the
value for the multivariate-t degrees of freedom parameter.
nobsvec
Vector of the total number of counts for each observation.
fixed.df
The degrees of freedom to be used for the multivariate-t
distribution. When this is specified, the DF will not be estimated.