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Adaptive exponential power distribution with moving estimator for nonstationary time series

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  • Jarek Duda

Abstract

While standard estimation assumes that all datapoints are from probability distribution of the same fixed parameters $\theta$, we will focus on maximum likelihood (ML) adaptive estimation for nonstationary time series: separately estimating parameters $\theta_T$ for each time $T$ based on the earlier values $(x_t)_{t

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  • Jarek Duda, 2020. "Adaptive exponential power distribution with moving estimator for nonstationary time series," Papers 2003.02149, arXiv.org, revised Mar 2020.
    • Handle: RePEc:arx:papers:2003.02149
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    References listed on IDEAS

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    1. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    2. Zhu, Dongming & Zinde-Walsh, Victoria, 2009. "Properties and estimation of asymmetric exponential power distribution," Journal of Econometrics, Elsevier, vol. 148(1), pages 86-99, January.
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    Cited by:

    1. Jarek Duda, 2023. "Adaptive Student's t-distribution with method of moments moving estimator for nonstationary time series," Papers 2304.03069, arXiv.org, revised Apr 2023.

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