| PICARD, Franck, Emily LEBARBIER, Eva BUDINSKÁ a Stephane ROBIN. Joint segmentation of multivariate Gaussian processes using mixed linear models. Computational Statistics & Data Analysis. ELSEVIER, 2011, roč. 55, č. 2, s. 1160-1170. ISSN 0167-9473. Dostupné z: https://dx.doi.org/10.1016/j.csda.2010.09.015. |
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@article{910438,
author = {Picard, Franck and Lebarbier, Emily and Budinská, Eva and Robin, Stephane},
article_number = {2},
doi = {http://dx.doi.org/10.1016/j.csda.2010.09.015},
keywords = {Segmentation; Mixed linear model; Multivariate Gaussian process; Dynamic programming; EM algorithm},
language = {eng},
issn = {0167-9473},
journal = {Computational Statistics & Data Analysis},
title = {Joint segmentation of multivariate Gaussian processes using mixed linear models.},
url = {http://pbil.univ-lyon1.fr/members/fpicard/franckpicard_fichiers/pdf/PLB11.pdf},
volume = {55},
year = {2011}
}
TY - JOUR
ID - 910438
AU - Picard, Franck - Lebarbier, Emily - Budinská, Eva - Robin, Stephane
PY - 2011
TI - Joint segmentation of multivariate Gaussian processes using mixed linear models.
JF - Computational Statistics & Data Analysis
VL - 55
IS - 2
SP - 1160-1170
EP - 1160-1170
PB - ELSEVIER
SN - 01679473
KW - Segmentation
KW - Mixed linear model
KW - Multivariate Gaussian process
KW - Dynamic programming
KW - EM algorithm
UR - http://pbil.univ-lyon1.fr/members/fpicard/franckpicard_fichiers/pdf/PLB11.pdf
L2 - http://pbil.univ-lyon1.fr/members/fpicard/franckpicard_fichiers/pdf/PLB11.pdf
N2 - The joint segmentation of multiple series is considered. A mixed linear model is used to account for both covariates and correlations between signals. An estimation algorithm based on EM which involves a new dynamic programming strategy for the segmentation step is proposed. The computational efficiency of this procedure is shown and its performance is assessed through simulation experiments. Applications are presented in the field of climatic data analysis.
ER -
PICARD, Franck, Emily LEBARBIER, Eva BUDINSKÁ a Stephane ROBIN. Joint segmentation of multivariate Gaussian processes using mixed linear models. \textit{Computational Statistics \&{} Data Analysis}. ELSEVIER, 2011, roč.~55, č.~2, s.~1160-1170. ISSN~0167-9473. Dostupné z: https://dx.doi.org/10.1016/j.csda.2010.09.015.
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