rcox {gRcox}R Documentation

Main function for specifying RCON/RCOR models

Description

This is the main function for specifying and fitting RCON/RCOR models in the package.

Usage

rcox(gm = NULL, vcc = NULL, ecc = NULL, type = c("rcon", "rcor"),
method = c("scoring", "ipm", "hyd", "user"),
fit = TRUE,
data = NULL, S = NULL, n = NULL, Kstart,
control = rcox.control())

Arguments

gm Generating class for a grapical Gaussian model, see 'Examples' for an illustration
vcc List of vertex colour classes for the model
ecc List of edge colour classes for the model
type Type of model. Default is RCON
method Estimation method. Default is 'scoring' which is stabilised Fisher scoring. An alternative is 'ipm' which is iterative partial maximisation. The methods 'hyd' and 'user' are for internal use and should not be called directly
fit Should the model be fitted
data A dataframe
S An empirical covariance matrix (as alternative to giving data as a dataframe)
n The number of observations (which is needed if data is specified as an empirical covariance matrix)
Kstart An initial value for K
control Controlling the fitting algorithms

Details

~~ If necessary, more details than the description above ~~

Value

A model object of type 'rcox'.

Author(s)

Søren Højsgaard, sorenh@agrsci.dk

Examples



[Package gRcox version 0.1 Index]