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Parameter Estimation and Subset Selection for Separable lower Triangular Bilinear Models

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  • Hai‐Bin Wang

Abstract

. Parameter estimation and subset selection for separable lower triangular bilinear (SLTBL) models are considered. Under a flat prior, we present an expectation–maximization (EM) algorithm to obtain the maximum likelihood estimation. Furthermore, two sub‐procedures are designed to select the best subset model after an initial fitting. Example with two simulated and one real data set illustrate the feasibility and validity of the proposed methods.

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  • Hai‐Bin Wang, 2005. "Parameter Estimation and Subset Selection for Separable lower Triangular Bilinear Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(5), pages 743-757, September.
    • Handle: RePEc:bla:jtsera:v:26:y:2005:i:5:p:743-757
    DOI: 10.1111/j.1467-9892.2005.00421.x
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    References listed on IDEAS

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    1. Dominique Guegan & Dinh Tuan Pham, 1992. "Power of the score test against bilinear time series models," Post-Print halshs-00199498, HAL.
    2. Won Kyung Kim & L. Billard & I. V. Basawa, 1990. "Estimation For The First‐Order Diagonal Bilinear Time Series Model," Journal of Time Series Analysis, Wiley Blackwell, vol. 11(3), pages 215-229, May.
    3. S. A. O. Sesay & T. Subba Rao, 1991. "DIFFERENCE EQUATIONS FOR HIGHER‐ORDER MOMENTS AND CUMULANTS FOR THE BILINEAR TIME SERIES MODEL BL(p, 0, p, 1)," Journal of Time Series Analysis, Wiley Blackwell, vol. 12(2), pages 159-177, March.
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    Cited by:

    1. Ping Chen & Jing Yang & Linyuan Li, 2015. "Synthetic detection of change point and outliers in bilinear time series models," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(2), pages 284-293, January.

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