Multivariate Normal Model Object

DESCRIPTION:

Class of objects that result from fitting multivariate normal models.

GENERATION:

This class of objects is returned as the paramIter component in the class "missmodel" object returned by the mdGauss, completeGauss, emGauss, and daGauss functions.

METHODS:

The class "Gauss" has associated methods: VarNames.Gauss, , , , , and .

STRUCTURE:

The class "Gauss" object consists of a matrix. Each row in the matrix represents one set of parameters estimates, typically produced using an iterative algorithm like EM or data augmentation. In the "Gauss" object, the parameters are the means and the Cholesky factorization of the variance-covariance matrix of a multivariate normal distribution. Using the control argument of Gauss, completeGauss, daGauss, or emGauss, you can choose which iterates to save. The iteration number for each row of saved estimates is given by the row name.

SPECIAL ATTRIBUTES:

VALUE:

colord
the order of the columns in the original matrix. This may differ from the order of the columns in the class "Gauss" object.
misscols
if TRUE, then the original data contained columns in which all observations were missing. Otherwise, the value FALSE.
varnames
a list of names for each of the variables in the original data, in the same order as in the original data.

SEE ALSO:

, , , .