bibtype C - Conference Paper (international conference)
ARLID 0450479
utime 20240111140910.5
mtime 20151119235959.9
title (primary) (eng) Mixture Multi-Step-Ahead Prediction
specification
page_count 12 s.
media_type E
serial
ARLID cav_un_epca*0450656
ISBN 978-618-5180-05-8
title Proceedings of the 16th conference of the Applied Stochastic Models and Data Analysis (ASMDA) International Society
page_num 727-738
publisher
place Piraeus
name ISAST: International Society for the Advancement of Science and Technology
year 2015
keyword mixture model
keyword mixture prediction
keyword recursive mixture estimation
keyword dynamic pointer
keyword active component
author (primary)
ARLID cav_un_auth*0101167
name1 Nagy
name2 Ivan
full_dept (cz) Zpracování signálů
full_dept (eng) Department of Signal Processing
department (cz) ZS
department (eng) ZS
institution UTIA-B
full_dept Department of Signal Processing
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0108105
name1 Suzdaleva
name2 Evgenia
full_dept (cz) Zpracování signálů
full_dept Department of Signal Processing
department (cz) ZS
department ZS
institution UTIA-B
full_dept Department of Signal Processing
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0274528
name1 Mlynářová
name2 Tereza
full_dept (cz) Zpracování signálů
full_dept Department of Signal Processing
department (cz) ZS
department ZS
institution UTIA-B
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
source_type pdf
url http://library.utia.cas.cz/separaty/2015/ZS/suzdaleva-0450479.pdf
cas_special
project
project_id GA15-03564S
agency GA ČR
ARLID cav_un_auth*0321440
project
project_id 7H14004
agency GA MŠk
ARLID cav_un_auth*0306850
project
project_id 7H14005
agency GA MŠk
country BE
ARLID cav_un_auth*0308433
abstract (eng) The presented paper deals with a task of the multi-step prediction with mixture models under Bayesian methodology. The main contribution of the paper is a recursive prediction algorithm for mixtures with the dynamic switching model. The proposed algorithm is based on construction of the weighting vector predicting the active component and its combination with data predictions from components. With the help of illustrative examples the paper compares the results with those obtained for the mixture prediction with the static switching model.
action
ARLID cav_un_auth*0322106
name The 16th conference of the Applied Stochastic Models and Data Analysis (ASMDA) International Society
place Piraeus
dates 30.06.2015-4.07.2015
country GR
reportyear 2016
RIV BB
num_of_auth 3
presentation_type PR
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0251934
confidential S
arlyear 2015
mrcbU56 pdf
mrcbU63 cav_un_epca*0450656 Proceedings of the 16th conference of the Applied Stochastic Models and Data Analysis (ASMDA) International Society 978-618-5180-05-8 727 738 Piraeus ISAST: International Society for the Advancement of Science and Technology 2015