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|Title:||MLE's bias pathology, model updated MLE, and Wallace's minimum message length method||Authors:||Yatracos, Yannis G.||Category:||Earth and Related Environmental Sciences||Field:||Engineering and Technology||Issue Date:||1-Mar-2015||Publisher:||Institute of Electrical and Electronics Engineers Inc.||Source:||IEEE Transactions on Information Theory Volume 61, Issue 3, 1 March 2015, Article number 6998937, Pages 1426-1431||metadata.dc.doi:||10.1109/TIT.2014.2386329||Abstract:||The inherent bias pathology of the maximum likelihood estimation method is confirmed for models with unknown parameters θ and ψ when maximum likelihood estimate (MLE) ψ is function of MLE θ. To reduce ψ's bias the likelihood equation to be solved for ψ is updated using the model for the data Y in it. For various models with ψ a shape parameter model updated (MU) MLE, ψMU, reduces ψ's bias. For the Pareto model ψMU reduces in addition ψ's variance. The results explain the difference that puzzled Fisher, between biased ψ and the unbiased estimate he obtained for two models with the abandoned two-stage procedure used in MUMLE's implementation. ψMU is also obtained with the minimum message length method thus motivating the use of priors in frequentist inference.||URI:||http://ktisis.cut.ac.cy/handle/10488/9383||ISSN:||00189448||Rights:||© 2014 IEEE.||Type:||Article|
|Appears in Collections:||Άρθρα/Articles|
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