Consistent Model Selection Procedure for Random Coefficient INAR Models.

ABSTRACT: In the realm of time series data analysis, information criteria constructed on the basis of likelihood functions serve as crucial instruments for determining the appropriate lag order. However, the intricate structure of random coefficient integer-valued time series models, which are founded on thinning operators, complicates the establishment of likelihood functions. Consequently, employing information criteria such as AIC and BIC for model selection becomes problematic. This study introduces an innovative methodology that formulates a penalized criterion by utilizing the estimation equation within conditional least squares estimation, effectively addressing the aforementioned challenge. Initially, the asymptotic properties of the penalized criterion are derived, followed by a numerical s

SUBMITTER: Yu K 

PROVIDER: S-EPMC10453110 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature