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Estimating function method for nonnegative autoregressive models

Author

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  • E. Hari Prasad
  • N. Balakrishna

Abstract

A stationary sequence of nonnegative random variables generated by autoregressive (AR) models may be used to describe the inter‐arrival times between events in counting processes. Even though, several such models are available in the literature, there is no unified approach to estimate their parameters. In this paper, we propose a class of combined estimating function method to estimate the model parameters of AR models with gamma marginals. The proposed method is compared with other estimation procedures and are illustrated by simulation and data analysis.

Suggested Citation

  • E. Hari Prasad & N. Balakrishna, 2023. "Estimating function method for nonnegative autoregressive models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 77(4), pages 471-496, November.
    • Handle: RePEc:bla:stanee:v:77:y:2023:i:4:p:471-496
    DOI: 10.1111/stan.12294
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    References listed on IDEAS

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    3. Božidar V. Popović & Miroslav M. Ristić & Narayana Balakrishna, 2017. "A mixed stationary autoregressive model with exponential marginals," Statistical Papers, Springer, vol. 58(4), pages 1125-1148, December.
    4. Wei†Cheng Hsiao & Hao†Yun Huang & Ching†Kang Ing, 2018. "Interval Estimation for a First†Order Positive Autoregressive Process," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(3), pages 447-467, May.
    5. Lengyi Han & W. John Braun & Jason Loeppky, 2020. "Random coefficient minification processes," Statistical Papers, Springer, vol. 61(4), pages 1741-1762, August.
    6. Hwang, S.Y. & Basawa, I.V., 2011. "Godambe estimating functions and asymptotic optimal inference," Statistics & Probability Letters, Elsevier, vol. 81(8), pages 1121-1127, August.
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