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http://hdl.handle.net/10773/16182
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Möller, Tobias | pt |
dc.contributor.author | Silva, M. Eduarda | pt |
dc.contributor.author | Weiss, Christian | pt |
dc.contributor.author | Scotto, Manuel González | pt |
dc.contributor.author | Pereira, Isabel | pt |
dc.date.accessioned | 2016-10-06T11:03:16Z | - |
dc.date.available | 2018-07-20T14:00:56Z | - |
dc.date.issued | 2016-10 | - |
dc.identifier.issn | 1863-818X | pt |
dc.identifier.uri | http://hdl.handle.net/10773/16182 | - |
dc.description.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. | pt |
dc.language.iso | eng | pt |
dc.publisher | Springer | pt |
dc.relation | FCT - UID/MAT/04106/2013 | pt |
dc.rights | openAccess | por |
dc.subject | Thinning operation | pt |
dc.subject | Threshold models | pt |
dc.subject | Binomial models | pt |
dc.subject | Count processes | pt |
dc.title | Self-exciting threshold binomial autoregressive processes | pt |
dc.type | article | pt |
dc.peerreviewed | yes | pt |
ua.distribution | international | pt |
degois.publication.firstPage | 369 | pt |
degois.publication.issue | 4 | pt |
degois.publication.lastPage | 400 | pt |
degois.publication.title | AStA Advances in Statistical Analysis | pt |
degois.publication.volume | 100 | pt |
dc.date.embargo | 2017-10-01T11:00:00Z | - |
dc.identifier.doi | 10.1007/s10182-015-0264-6 | pt |
Appears in Collections: | CIDMA - Artigos |
Files in This Item:
File | Description | Size | Format | |
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j2015_ASta.pdf | Main article | 640.92 kB | Adobe PDF | View/Open |
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