0410855 20240903203903.520060210235959.9 19 s. cav_un_epca*02971951387-087452 (2002)179-197 spectral density Gauss-Markov random fields maximum pseudolikelihood estimate cav_un_auth*0101114 Janžura Martin UTIA-B Department of Stochastic Informatics Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101069 Boček Pavel UTIA-B Department of Stochastic Informatics Ústav teorie informace a automatizace AV ČR, v. v. i. 12B GA201/99/0269 GA ČR cav_un_auth*0005940 GA102/99/1137 GA ČR cav_un_auth*0004432 CEZ:AV0Z1075907 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. BB SI http://hdl.handle.net/11104/0130942 UTIA-B 20020069 2002 cav_un_epca*0297195 Statistical Inference for Stochastic Processes 1387-0874 1572-9311 Roč. 5 č. 2 2002 179 197