bibtype J - Journal Article
ARLID 0310659
utime 20240103190300.1
mtime 20090325235959.9
WOS 000258589700006
DOI 10.1080/00949650701282507
title (primary) (eng) Assessing the performance of variational methods for mixed logistic regression models
specification
page_count 15 s.
serial
ARLID cav_un_epca*0254060
ISSN 0094-9655
title Journal of Statistical Computation and Simulation
volume_id 78
volume 8 (2008)
page_num 765-779
publisher
name Taylor & Francis
title (cze) Studium chování variačních metod pro směsové modely logistické regrese
keyword Mixed models
keyword Logistic regression
keyword Variational methods
keyword Lower bound approximation
author (primary)
ARLID cav_un_auth*0241186
name1 Rijmen
name2 F.
country BE
author
ARLID cav_un_auth*0101228
name1 Vomlel
name2 Jiří
institution UTIA-B
full_dept Department of Decision Making Theory
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
cas_special
project
project_id 1M0572
agency GA MŠk
ARLID cav_un_auth*0001814
project
project_id 2C06019
agency GA MŠk
country CZ
ARLID cav_un_auth*0216518
research CEZ:AV0Z10750506
abstract (eng) We present a variational estimation method for the mixed logistic regression model. The method is based on a lower bound approximation of the logistic function [Jaakkola, J.S. and Jordan, M.I., 2000].
abstract (cze) V práci je navžena variační metoda pro směsové modely logistické regrese. Metoda je založena na aproximaci logistické funkce pomocí její gaussovské dolní meze [Jaakkola, J.S. a Jordan, M.I., 2000].
reportyear 2009
RIV BB
permalink http://hdl.handle.net/11104/0162453
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arlyear 2008
mrcbU34 000258589700006 WOS
mrcbU63 cav_un_epca*0254060 Journal of Statistical Computation and Simulation 0094-9655 1563-5163 Roč. 78 č. 8 2008 765 779 Taylor & Francis