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Estimation in nonlinear random fields models of autoregressive type with random parameters

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  • Amel Saidi
  • Abdelghani Hamaz
  • Ouerdia Arezki

Abstract

In this article, we present new original theoretical results on estimation in nonlinear random field models. We focus on two dimensionally indexed random coefficients autoregressive model with order (p1,p2)∈N2, 2D−RCAR(p1,p2) for short. We first develop a maximum likelihood estimation procedure for estimating the unknown parameters of 2D−RCAR(p1,p2). Moreover, we prove that the estimates are strongly consistent. Finally, these results are then applied to construct efficient estimates in 2D-RCAR model of order (0, 1). Then, a simulation part is given to illustrate the effectiveness and accuracy of the estimates.

Suggested Citation

  • Amel Saidi & Abdelghani Hamaz & Ouerdia Arezki, 2024. "Estimation in nonlinear random fields models of autoregressive type with random parameters," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 53(1), pages 294-309, January.
    • Handle: RePEc:taf:lstaxx:v:53:y:2024:i:1:p:294-309
    DOI: 10.1080/03610926.2022.2077962
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