hllm {gRbase}R Documentation

Hierarchical log-linear models

Description

An implementation of hierarchical log-linear models using the framework of gRbase. A model object is defined using hllm, fitted using fit (which calls loglm) and a model search performed using stepwise. The models may be displayed and manipulated using the gRbase functions, eg. dynamic.Graph.

Usage

hllm(formula = ~.^1, gmData, marginal)

Arguments

formula an object of class formula. The right hand side of the formula is a list of the generators separated by +. A generator is specified by variable names with separated by *. Commonly used models have short hand notations: saturated model (~.^.), main effects (~.^1), all k'th order interactions (~.^k).
gmData an object of class gmData.
marginal an optional argument specifying a subset of the variables from the gmData object.

Value

hllm returns an object of class hllm, inheriting from the superclass gModel.

Author(s)

Søren Højsgaard, sorenh@agrsci.dk,
Claus Dethlefsen, cld@rn.dk

See Also

gmData, gRfit, ggm, dynamic.Graph

Examples

data(reinis)
reinis <- as.gmData(reinis)
m2 <-
hllm(~smoke*phys*protein+mental*phys+mental*family+smoke*systol*protein,
reinis)
m2 <- fit(m2,engine="loglm")
## Not run: dynamic.Graph(m2)

[Package gRbase version 0.1.25 Index]