LLdecomp-package {LLdecomp}R Documentation

The main function "decompfit" decomposes discrete variable into cliques and separators.

Description

The main function "decompfit" takes as input a matrix consisting of discrete variables. Decomposes these using Random Forests and the Message Passing algorithm into cliques and separators. These can then be used to fit a log-linear model. The whole procedure is described in http://arxiv.org/abs/0904.1510.

Details

Package: LLdecomp
Type: Package
Version: 1.0
Date: 2009-05-12
License: GPL
LazyLoad: yes

Please note that this is an *early test release*.

The best entry point for the package are the examples in the help file of the function decompfit. Index: Index:

  logilasso                 Fits a loglinear model or/and performs
                            cross-validation
  levelcv                   Performs cross-validation for the specified
                            number of interactions
  traceplot                 Plots the solution path from lambdamax to lambdamin for
                            all components of the solution vector beta
  graphmod                  Plots a graphical model
  plot.logilasso            Plot method for a logilasso object
  predict.logilasso         Predict method for a logilasso object

Author(s)

Corinne Dahinden

Maintainer: Corinne Dahinden <dahinden@stat.math.ethz.ch>

References

http://arxiv.org/abs/0904.1510

Examples

## Data generation where the first and second variables are dependent.
data1 <- matrix(NA,nrow=200,ncol=5)
data1[,-1] <- sample(c(0,1),200*4,replace=TRUE)
prob <- data1[,2]*0.6+0.2
data1[,1] <- rbinom(200,1,prob)

dfit <- decompfit(data1,3)

[Package LLdecomp version 1.0 Index]