An Exploratory Analysis of Multiple Multivariate Time Series

0 avis

An Exploratory Analysis of Multiple Multivariate Time Series

Archive ouverte

Billard, Lynne | Douzal-Chouakria, Ahlame | Seyed, Yaser

Edité par CCSD -

International audience. Our aim is to extend standard principal component analysis for non-time series data to explore and highlight the main structure of multiple sets of multivariate time series. To this end, standard variance- covariance matrices are generalized to lagged cross-autocorrelation ma- trices. The methodology produces principal component time series, which can be analysed in the usual way on a principal component plot, except that the plot also includes time as an additional dimension.

Langue: en

Indexation

Consulter en ligne

Consulter le document

Suggestions

Du même auteur

Principal Component Analysis for Interval-Valued Observations

Archive ouverte | Douzal-Chouakria, Ahlame | CCSD

International audience. One feature of contemporary datasets is that instead of the single point value in the p-dimensional space p seen in classical data, the data may take interval values thus producing hypercubes...

Classification and Regression Trees on Aggregate Data Modeling: An Application in Acute Myocardial Infarction

Archive ouverte | Quantin, C. | CCSD

International audience. Cardiologists are interested in determining whether the type of hospital pathway followed by a patient is predictive of survival. The study objective was to determine whether accounting for h...

Copula analysis of mixture models

Archive ouverte | Vrac, Mathieu | CCSD

International audience. Contemporary computers collect databases that can be too large for classical methods to handle. The present work takes data whose observations are distribution functions (rather than the sing...

Chargement des enrichissements...