MDPCA : Moving Dynamic Principal Component Analysis for Non-Stationary Multivariate Time Series

Alshammri, Fayed Awdah M (2020) MDPCA : Moving Dynamic Principal Component Analysis for Non-Stationary Multivariate Time Series. University of Strathclyde, Glasgow.

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Abstract

This function reduce the dimension of non-stationary (and stationary) multivariate time series by performing eigenanalysis on the moving cross-covriance matrix of the extended data matrix up to some specified lag. Notice that thefollowing libraries are needed to be installed before using the MDPCA function: library(roll); library(expm).

  • Item type:Other
    ID code:71849
    Dates:
    Date
    Event
    10 March 2020
    Published
    Notes:Alshammri, F. (2020). MDPCA: Moving Dynamic Principal Component Analysis for Non-Stationary Multivariate Time Series. R package version 0.1.0.
    Subjects:Science > Mathematics > Computer software
    Department:Faculty of Science > Mathematics and Statistics
    Depositing user: Pure Administrator
    Date deposited:24 Mar 2020 10:00
    Last modified:18 Apr 2024 00:46
    URI:https://strathprints.strath.ac.uk/id/eprint/71849
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