Joint segmentation of multivariate Gaussian processes using mixed linear models.

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PICARD Franck LEBARBIER Emily BUDINSKÁ Eva ROBIN Stephane

Rok publikování 2011
Druh Článek v odborném periodiku
Časopis / Zdroj Computational Statistics & Data Analysis
Fakulta / Pracoviště MU

Lékařská fakulta

Citace
www Odkaz na stiahnutie článku
Doi http://dx.doi.org/10.1016/j.csda.2010.09.015
Obor Aplikovaná statistika, operační výzkum
Klíčová slova Segmentation; Mixed linear model; Multivariate Gaussian process; Dynamic programming; EM algorithm
Popis 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.

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