Graphical Data Analysis withR

Unidimensional data: A graphical analysis

The purpose of this article is three-fold: to demonstrate the interface between the theory of scaling and graph theory, to determine the class of unidimensional graphs, and to provide a method for analyzing data which consists cf both dominance and indifference relations. The most definitive work on the subject of data analysis is Coombs’ (1976) A Theory of Data in which eight types of data are...

Comparison of Graphical Data Analysis Methods

Ordinal Data Analysis via Graphical Models

Background. Undirected graphical models or Markov random fields (MRFs) are very popular for modeling multivariate probability distributions. A considerable amount of work on MRFs has focused on modeling continuous variables and unordered categorical variables also called as nominal variables. However, data from many real world applications involve ordered categorical variables also called as or...

MGraph: graphical models for microarray data analysis

UNLABELLED This paper introduces a MATLAB toolbox, MGraph, which applies graphical models as a natural environment to formulate and solve problems in microarray data analysis. MGraph with its graphical interface allows the user to predict genetic regulatory networks by a graphical gaussian model (GGM), and to quantify the effects of different experimental treatment conditions on gene expression...

Software for data analysis with graphical models

Wray L. Buntine RIACS at NASA Ames Research Center Mail Stop 269{2, Mo ett Field, CA 94035{1000, USA [email protected] H. Scott Roy Heuristicrats Research, Inc. 1678 Shattuck Avenue, Suite 310, Berkeley, CA 94709-1631, USA [email protected] Abstract Probabilistic graphical models are being used widely in arti cial intelligence and statistics, for instance, in diagnosis and expert syst...