bibtype J - Journal Article
ARLID 0410855
utime 20240903203903.5
mtime 20060210235959.9
title (primary) (eng) Relative asymptotic efficiency of the maximum pseudolikelihood estimate for Gauss-Markov random fields
specification
page_count 19 s.
serial
ARLID cav_un_epca*0297195
ISSN 1387-0874
title Statistical Inference for Stochastic Processes
volume_id 5
volume 2 (2002)
page_num 179-197
keyword spectral density
keyword Gauss-Markov random fields
keyword maximum pseudolikelihood estimate
author (primary)
ARLID cav_un_auth*0101114
name1 Janžura
name2 Martin
institution UTIA-B
full_dept Department of Stochastic Informatics
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101069
name1 Boček
name2 Pavel
institution UTIA-B
full_dept Department of Stochastic Informatics
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
COSATI 12B
cas_special
project
project_id GA201/99/0269
agency GA ČR
ARLID cav_un_auth*0005940
project
project_id GA102/99/1137
agency GA ČR
ARLID cav_un_auth*0004432
research CEZ:AV0Z1075907
abstract (eng) A general version of the maximum pseudolikelihood estimate of parameters within the class of Gauss-Markov random fields is stated in a rigorous way. Its asymptotic properties, namely the consistency, the asymptotic normality, and the relative asymptotic efficiency are studied.Explicit formulas for the asymptotic covariance matrix are given, and a decrease of efficiency is proved. A numerical example is added to show that the efficiency can be improved by enlarging the range of the conditional distribution.
RIV BB
department SI
permalink http://hdl.handle.net/11104/0130942
ID_orig UTIA-B 20020069
arlyear 2002
mrcbU63 cav_un_epca*0297195 Statistical Inference for Stochastic Processes 1387-0874 1572-9311 Roč. 5 č. 2 2002 179 197