2005/07/31 by Djalil Chafaï, Djalil Chafai, Didier Concordet
Computer Science · Engineering · Mathematics · #Applied mathematics #Asymptotic analysis #Asymptotic distribution #Bayesian Methods and Mixture Models #Calculus (dental) #Consistency (knowledge bases) #Contraction (grammar) #Control Systems and Identification #Discrete mathematics #Estimator #Mathematical proof #Mathematics #Statistical Methods and Inference #Statistics #Strong consistency #Weak consistency #math.PR #math.ST #msc:34K29 #msc:60F99 #msc:62F12 #msc:62G05 #sort #stat.TH
paper · pdf · doi:10.1016/j.jspi.2006.09.027
published as Journal of Statistical Planning and Inference 137, 9 (2007) 2774-2783 · Accepted for publication in Journal of Statistical Planning and Inference
arxiv created 2006/09/15 · openalex publication_date 2007/02/12 · arxiv updated 2009/12/01 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/05
The aim of this article is to simplify Pfanzagl's proof of consistency for asymptotic maximum likelihood estimators, and to extend it to more general asymptotic M-estimators. The method relies on the existence of a sort of contraction of the parameter space which admits the true parameter as a fixed point. The proofs are short and elementary.