Maximum Likelihood Estimation in Gaussian Chain Graph Models under the Alternative Markov Property

Mathias Drton and Michael Eichler

Scandinavian Journal of Statistics, 2006, vol. 33, issue 2, 247-257

Abstract: Abstract. The Andersson–Madigan–Perlman (AMP) Markov property is a recently proposed alternative Markov property (AMP) for chain graphs. In the case of continuous variables with a joint multivariate Gaussian distribution, it is the AMP rather than the earlier introduced Lauritzen–Wermuth–Frydenberg Markov property that is coherent with data‐generation by natural block‐recursive regressions. In this paper, we show that maximum likelihood estimates in Gaussian AMP chain graph models can be obtained by combining generalized least squares and iterative proportional fitting to an iterative algorithm. In an appendix, we give useful convergence results for iterative partial maximization algorithms that apply in particular to the described algorithm.

Date: 2006
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Persistent link: https://EconPapers.repec.org/RePEc:bla:scjsta:v:33:y:2006:i:2:p:247-257

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