Asymptotic properties of a stochastic EM algorithm for mixtures with censored data
2010 (English)In: Journal of Statistical Planning and Inference, ISSN 0378-3758, Vol. 140, no 1, 111-127 p.Article in journal (Refereed) Published
Weak consistency and asymptotic normality is shown for a stochastic EM algorithm for censored data from a mixture of distributions under lognormal assumptions. The asymptotic properties hold for all parameters of the distributions, including the mixing parameter. In order to make parameter estimation meaningful it is necessary to know that the censored mixture distribution is identifiable. General conditions under which this is the case are given. The stochastic EM algorithm addressed in this paper is used for estimation of wood fibre length distributions based on optically measured data from cylindric wood samples (increment cores).
Place, publisher, year, edition, pages
Elsevier , 2010. Vol. 140, no 1, 111-127 p.
Censoring; Fibre length distribution; Identifiability; Increment core; Mixture; Stochastic EM algorithm
Mathematics Probability Theory and Statistics
Research subject Mathematical Statistics; Statistics
IdentifiersURN: urn:nbn:se:umu:diva-29776DOI: 10.1016/j.jspi.2009.06.014ISI: 000271354300010OAI: oai:DiVA.org:umu-29776DiVA: diva2:278112