Parameters Estimation in Non-Negative Integer-Valued Time Series: Approach Based on Probability Generating Functions
نویسندگان
چکیده
This manuscript deals with a parameter estimation of non-negative integer-valued (NNIV) time series based on the so-called probability generating function (PGF) method. The theoretical background PGF technique for very general, stationary class NNIV is described, as well asymptotic properties obtained estimates. After that, particular emphasis given to estimators independent identical distributed (IID) and autoregressive (INAR) series. A Monte Carlo study thus estimates, numerical integration appropriate objective function, also presented. For this purpose, quadrature formulas were computed using Gegenbauer orthogonal polynomials. Finally, application in dynamic analysis some actual data given.
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ژورنال
عنوان ژورنال: Axioms
سال: 2023
ISSN: ['2075-1680']
DOI: https://doi.org/10.3390/axioms12020112