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Self-exciting threshold autoregressive model based generalized binomial thinning operator
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DOI：10.1080/03610918.2026.2658741.png)
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Abstract
En 中文
In this paper, we introduce an integer-valued threshold process that incorporates a random perturbation term with a negative binomial distribution, based on a generalized binomial thinning operator. We discuss the fundamental probabilistic and statistical properties of the model. The conditional least squares estimator and the conditional maximum likelihood estimator are examined for two scenarios: the threshold variable is known and unknown. Additionally, we derive the asymptotic properties of these estimators. Finally, the paper presents a numerical analysis of the estimation results as well as an example with real data.
Keywords:
Generalized binomial thinning operator
Integer-valued time series
Parameter estimation
Threshold model
Journal
C
IF:
0.8
Papers:
213
Citations:
4.7K