fit: Fit RCOX models

In gRc: Inference in Graphical Gaussian Models with Edge and Vertex Symmetries

Description

This is a general function for fitting RCOX models (i.e.\ RCON and RCOR models) using different estimation algorithms.

Usage

## S3 method for class 'rcox'
fit(object, Kstart=object$Kstart, method = object$method, control = object$control,
details = object$details, trace = object$trace, returnModel = TRUE,...)

Arguments

object	An RCOX model object (an object of class 'rcox')
Kstart	An initial value for the concentration matrix.
method	The specific estimation method. Can be either "scoring", (a modified Fisher scoring algorithm), "ipm" (iterative partial maximization), "matching" (score matching) or "user" (currently not used)
control	A list controlling the fitting algorithms. See the 'details' section.
details	The amount of details printed on the screen. 0 means no details at all.
trace	Controls various diagnostics print outs. A debugging feature not intended for the user.
returnModel	If TRUE the model object m is returned with fitting info added to it. If FALSE only the fitting info is returned.
...	Additional arguments; currently not used.

Details

The fitted parameters etc. can be extracted using 'fitInfo(m)'.

The control argument is a list with named entries. Most important are the entries 'maxouter' and 'maxinner' (which both defaults to 25) for controlling the estimation algorithms. For other components please refer to the code.

Value

An RCOX model object.

Author(s)

S<f8>ren H<f8>jsgaard, [e-mail]

See Also

rcox, update.rcox

Examples

data(math)
gm  = ~al:an:st
vcc = list(~me+st, ~ve+an, ~al)
ecc = list(~me:ve+me:al, ~ve:al+al:st)

m1 <- rcox(gm=gm, vcc=vcc, ecc=ecc, data=math, fit=FALSE)

fit(m1, method="matching")
fit(m1, method="scoring")
fit(m1, method="ipm")

## MISSING

gRc documentation built on May 2, 2019, 5:22 p.m.