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Showing 1 to 8 of 8 for “"Functional time series"”.

  1. Changepoint detection and estimation for spatially indexed functional time series

    Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2025-05-01

    uiuc Repository record for Changepoint detection and estimation for spatially indexed functional time series (opens in a new tab)

  2. Test of change point versus long-range dependence in functional time series

    In scalar time series analysis, a long-range dependent (LRD) series cannot be easily distinguished from certain non-stationary models, such as the change in mean model with short-range dependent (SRD) errors. To be specific, realizations of LRD series usually have a characteristic of changing local …

    colostate Repository record for Test of change point versus long-range dependence in functional time series (opens in a new tab)

  3. Likelihood Ratio Combination of Multiple Biomarkers and Change Point Detection in Functional Time Series

    … in medical research. Change point detection for functional time series has attracted considerable attention from researchers. Existing methods either rely on FPCA, which may perform poorly with complex data, or use bootstrap approaches in forms that fall short in effectively detecting diverse …

    vt Repository record for Likelihood Ratio Combination of Multiple Biomarkers and Change Point Detection in Functional Time Series (opens in a new tab)

  4. Bayesian population inference for effective connectivity

    … (MAR) process is proposed to jointly model functional neuroimaging time series collected from multiple subjects, and to characterize the distribution of MAR coefficients across the population from which those subjects were drawn. Thus, model-based inference about the interaction between …

    mit Repository record for Bayesian population inference for effective connectivity (opens in a new tab)

  5. Shape based classification and functional forecast of traffic flow profiles

    … accidents, congestion behavior, peak time fluctuations, and malfunctioning sensors.</p><p>To ascertain the significance of shape in traffic analysis, the proposed methodology was validated through a comparative classification analysis of the original data and GSD transformed data using …

    must-thes Repository record for Shape based classification and functional forecast of traffic flow profiles (opens in a new tab)

  6. Statistical inference for dependent data

    Functional data Analysis has emerged as an important area of statistics which provides convenient and informative tool for the analysis of data objects of high dimension/high resolution. In the literature, it seems that the emphasis has been placed on independent functional data or models where the …

    uiuc Repository record for Statistical inference for dependent data (opens in a new tab)

  7. Bayesian analysis of historical functional linear models with application to air pollution forecasting

    Historical functional linear models are used to analyse the relationship between a functional response and a functional predictor whereby only the past of the predictor process can affect the current outcome. In this work, we develop a Bayesian framework for the analysis of the historical …

    cape-town Repository record for Bayesian analysis of historical functional linear models with application to air pollution forecasting (opens in a new tab)

  8. STATISTICAL MODELING FOR COMPLEX FUNCTIONAL AND NETWORK TIME SERIES DATA

    Functional and network time series data have been available, which provide richer information that brings opportunities and potentials to solve scientific problems. On the other hand, the complex structure presents challenges to conventional statistical analytical tools in terms of estimation and …

    nus Repository record for STATISTICAL MODELING FOR COMPLEX FUNCTIONAL AND NETWORK TIME SERIES DATA (opens in a new tab)