Saddlepoint Method in Integer-valued Bilinear Models

Document Type : Original Article

Authors
Mehrnaz Mohammadpour
Rana Bamdadi
Department of Statistics, Faculty of Mathematical Sciences, University of Mazandaran, Babolsar, Iran.
10.22034/jirss.2024.2020805.1048
Abstract
Saddlepoint techniques have proven effective across various applications due to their markable accuracy in approximating densities. In this work, through considering the integer-valued bilinear model, the saddlepoint maximum likelihood method is applied to parameter estimation. Simulation studies show that this method provides an efficient approach to parameter estimation. The analysis of practical cases highlight the usefulness and adequacy of the proposed model in applications.
Keywords
Integer-valued Bilinear Process
Quasi-Likelihood
Saddlepoint Approximation
Thinning Operator
Subjects
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Journal of the Iranian Statistical Society
Volume 23, Issue 1
June 2024
Pages 51-62

  • Receive Date 20 January 2024
  • Revise Date 08 October 2024
  • Accept Date 11 October 2024