0346969 20240103193823.820100914235959.9 000287979900102 7 s. cav_un_epca*0346968978-80-7394-218-2602-608České BudějoviceUniversity of South Bohemia, Faculty of Economics2010HoudaMichalFriebelováJana auto-regression robust parameter estimation cav_un_auth*0263960 Šindelář Jan Adaptivní systémy Department of Adaptive Systems AS AS UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2010/AS/sindelar-bayesian vector auto-regression model with laplace errors applied to financial market data.pdf 1M0572 GA MŠk cav_un_auth*0001814 GA102/08/0567 GA ČR cav_un_auth*0239566 CEZ:AV0Z10750506 The article presents alternative version of Bayesian vector auto-regression model with Laplace distributed innovations. Bayesian estimation in such model is more computationally demanding than estimation in a model with normally distributed innovations, but because of the heavier tails of Laplace distribution, it is more robust. In the article I try to present the way of proceeding with the estimation, obtaining a full posterior distribution of the parameters as a result. At the end an efficient algorithm is sketched, but this part of the research is still unfinished. cav_un_auth*0263925 Mathematical Methods in Economics 2010 České Budějovice 08.09.2010-10.09.2010 CZ 2011 BB http://hdl.handle.net/11104/0187854 2010 000287979900102 WOS cav_un_epca*0346968 Proceedings of Mathematical Methods in Economics 2010 978-80-7394-218-2 602 608 České Budějovice University of South Bohemia, Faculty of Economics 2010 Houda Michal 340 Friebelová Jana 340