mmlt-methods: Methods for mmlt Objects

Description

Methods for objects of class mmlt

Usage

# S3 method for mmlt
weights(object, ...)
# S3 method for mmlt
logLik(object, parm = coef(object, fixed = FALSE), w = NULL, newdata = NULL, ...)
# S3 method for mmlt
vcov(object, parm = coef(object, fixed = FALSE), complete = FALSE, ...)
# S3 method for mmlt
Hessian(object, parm = coef(object, fixed = FALSE), ...)
# S3 method for mmlt
Gradient(object, parm = coef(object, fixed = FALSE), ...)
# S3 method for mmlt
estfun(x, parm = coef(x, fixed = FALSE),
       w = NULL, newdata = NULL, ...)
# S3 method for mmlt
mkgrid(object, ...)
# S3 method for mmlt
variable.names(object, response_only = FALSE, ...)

Arguments

object, x: a fitted multivariate transformation model as returned by mmlt
fixed: a logical indicating if only estimated coefficients (fixed = FALSE) should be returned OR (for update) a named vector of fixed regression coefficients; the names need to correspond to column names of the design matrix
parm: model parameters
w: model weights
weights: model weights
newdata: an optional data frame of new observations. Allows evaluation of the log-likelihood for a given model object on these new observations. The parameters parm and w are ignored in this situation.
response_only: only return the names of the response variables
complete: currently ignored
...: additional arguments

Details

coef can be used to get and set model parameters, weights and logLik extract weights and evaluate the log-likelihood (also for parameters other than the maximum likelihood estimate). Hessian returns the Hessian (of the negative log-likelihood) and vcov the inverse thereof. Gradient gives the negative gradient (minus sum of the score contributions) and estfun the negative score contribution by each observation. mkgrid generates a grid of all variables (as returned by variable.names) in the model.