TR announcement (IPF for conditionals)

[Hermann Von Hasseln]

In connection with the recent announcement of Padhraic Smyth et al.
("Probabilistic Independence Networks For Hideen Markov Probability Models")
I'd like to announce the following technical report, which might be of
interest for you:


	AN IPF PROCEDURE FOR MIXED GRAPHICAL MODELS

	            Hermann von Hasseln
			    IMPA
         Instituto de Matem\'atica Pura e Aplicada 
		   Rio de Janeiro, Brazil


			   Abstract

  We introduce a variant of the well--known iterative 
  proportional fitting (IPF) procedure. Just as the traditional 
  IPF procedure, which uses a given set of marginal probabilities 
  as constraints that have to be satisfied in each iteration, 
  we show that this also can be done with a given set of compatible 
  conditional probabilities. In the case of compatible conditionals 
  convergence is guaranteed by a theorem by Csisz\'ar. We also 
  define a ``mixed'' version of IPF procedures, where the set of 
  constraints is given by a mixed set of marginal and conditional 
  probabilities.
  
  Keywords: Iterative proportional fitting, maximum likelihood estimation, 
  graphical models, maximum entropy, minimum discrimination
  information, conditionally specified distributions.


To obtain a copy of these papers, pl. send your email request to
hermann at impa.br

Comments are welcome.


Hermann von Hasseln