Abstract
The random environment integer-valued autoregressive models of higher orders introduced by Nastic et al. (J Time Ser Anal 37: 267–287, 2016) are generalized. Generalizations are made by relaxing two assumptions: the assumption about the equality of negative binomial thinning operators and the assumption that the maximal orders are equal for all the process random states. Some statistical properties of the introduced models are derived and discussed. Their unknown parameters are estimated by the Yule–Walker method and the performances of the obtained estimators are checked using simulated data sets. A possible application of the models on the real-life data is discussed at the end of the paper.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
