Self-exciting threshold binomial autoregressive processes

Tobias A. Möller (), Maria Eduarda Silva (), Christian H. Weiß (), Manuel G. Scotto () and Isabel Pereira ()
Additional contact information
Tobias A. Möller: Helmut Schmidt University
Maria Eduarda Silva: University of Porto
Christian H. Weiß: Helmut Schmidt University
Manuel G. Scotto: IST University of Lisbon
Isabel Pereira: University of Aveiro

AStA Advances in Statistical Analysis, 2016, vol. 100, issue 4, No 1, 369-400

Abstract: Abstract We introduce a new class of integer-valued self-exciting threshold models, which is based on the binomial autoregressive model of order one as introduced by McKenzie (Water Resour Bull 21:645–650, 1985. doi: 10.1111/j.1752-1688.1985.tb05379.x ). Basic probabilistic and statistical properties of this class of models are discussed. Moreover, parameter estimation and forecasting are addressed. Finally, the performance of these models is illustrated through a simulation study and an empirical application to a set of measle cases in Germany.

Keywords: Thinning operation; Threshold models; Binomial models; Count processes (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://link.springer.com/10.1007/s10182-015-0264-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:alstar:v:100:y:2016:i:4:d:10.1007_s10182-015-0264-6

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10182/PS2

DOI: 10.1007/s10182-015-0264-6

Access Statistics for this article

AStA Advances in Statistical Analysis is currently edited by Göran Kauermann and Yarema Okhrin

More articles in AStA Advances in Statistical Analysis from Springer, German Statistical Society
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().