BIROn - Birkbeck Institutional Research Online

    Simulation methodology for inference on physical parameters of complex vector-valued signals

    Chandna, Swati and Walden, A. (2013) Simulation methodology for inference on physical parameters of complex vector-valued signals. IEEE Transactions on Signal Processing 61 (21), pp. 5260-5269. ISSN 1053-587X.

    [img]
    Preview
    Text
    ChandnaWalden2013.pdf - Author's Accepted Manuscript

    Download (1MB) | Preview

    Abstract

    Complex-valued vector time series occur in diverse fields such as oceanography and meteorology, and scientifically interpretable parameters may be estimated from them. We show that it is possible to make inference such as confidence intervals on these parameters using a vector-valued circulant embedding simulation method, combined with bootstrapping. We apply the methodology to three parameters of interest in oceanography, and compare the resulting simulated confidence intervals with those computed using analytic results. We conclude that the simulation scheme offers an inference approach either in the absence of theoretical distributional results, or to check the effect of nuisance parameters where theoretical results are available.

    Metadata

    Item Type: Article
    Additional Information: (c) 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
    School: Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
    Depositing User: Swati Chandna
    Date Deposited: 04 Jan 2019 13:24
    Last Modified: 09 Aug 2023 12:45
    URI: https://eprints.bbk.ac.uk/id/eprint/25636

    Statistics

    Activity Overview
    6 month trend
    258Downloads
    6 month trend
    251Hits

    Additional statistics are available via IRStats2.

    Archive Staff Only (login required)

    Edit/View Item Edit/View Item