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- Title
Randomness Test of Thinning Parameters for the NBRCINAR(1) Process.
- Authors
Zhang, Shuanghong
- Abstract
Non-negative integer-valued time series are usually encountered in practice, and a variety of integer-valued autoregressive processes based on various thinning operators are commonly used to model these count data with temporal dependence. In this paper, we consider a first-order integer-valued autoregressive process constructed by the negative binomial thinning operator with random coefficients, to address the problem of constant thinning parameters which might not always accurately represent real-world settings because of numerous external and internal causes. We estimate the model parameters of interest by the two-step conditional least squares method, obtain the asymptotic behaviors of the estimators, and furthermore devise a technique to test the constancy of the thinning parameters, which is essential for determining whether or not the proposed model should consider the parameters' randomness. The effectiveness and dependability of the suggested approach are illustrated by a series of thorough simulation studies. Finally, two real-world data analysis examples reveal that the suggested approach is very useful and flexible for applications.
- Subjects
LEAST squares; AUTOREGRESSIVE models; RANDOM operators; TIME series analysis; DATA analysis; VALIDITY of statistics
- Publication
Axioms (2075-1680), 2024, Vol 13, Issue 4, p260
- ISSN
2075-1680
- Publication type
Article
- DOI
10.3390/axioms13040260