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dc.contributor.authorHudecová, Sárka
dc.contributor.authorMeintanis, Simos G.
dc.contributor.authorHusková, Marie
dc.date.accessioned2016-09-02T12:51:06Z
dc.date.available2016-09-02T12:51:06Z
dc.date.issued2015
dc.identifier.citationHudecová, S. et al. 2015. Tests for time series of counts based on the probability-generating function. Statistics, 49(2):316-337. [http://dx.doi.org/10.1080/02331888.2014.979826]en_US
dc.identifier.issn0233-1888
dc.identifier.issn1029-4910 (Online)
dc.identifier.urihttp://hdl.handle.net/10394/18523
dc.identifier.urihttps://www.tandfonline.com/doi/full/10.1080/02331888.2014.979826
dc.identifier.urihttps://doi.org/10.1080/02331888.2014.979826
dc.description.abstractWe propose testing procedures for the hypothesis that a given set of discrete observations may be formulated as a particular time series of counts with a specific conditional law. The new test statistics incorporate the empirical probability-generating function computed from the observations. Special emphasis is given to the popular models of integer autoregression and Poisson autoregression. The asymptotic properties of the proposed test statistics are studied under the null hypothesis as well as under alternatives. A Monte Carlo power study on bootstrap versions of the new methods is included as well as real-data examplesen_US
dc.language.isoenen_US
dc.publisherTaylor & Francisen_US
dc.subjectINAR modelen_US
dc.subjectPoisson autoregressionen_US
dc.subjectGoodness-of-fit testen_US
dc.subjectEmpirical probability-generating functionen_US
dc.titleTests for time series of counts based on the probability-generating functions for time series of counts based on the probability-generating functionen_US
dc.typeArticleen_US
dc.contributor.researchID21262977 - Meintanis, Simos George


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