Partial Likelihood Analysis of Categorical Time Series Models

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dc.contributor.authorFakianos, Konstantinosen_US
dc.contributor.authorKedem, Benjaminen_US
dc.contributor.authorShort, David A.en_US
dc.contributor.departmentISRen_US
dc.date.accessioned2007-05-23T09:59:42Z
dc.date.available2007-05-23T09:59:42Z
dc.date.issued1995en_US
dc.description.abstractPartial likelihood analysis of two generalized logistic regression models for nominal and ordinal categorical time series is presented, taking into account stochastic time-dependent covariates. Under some conditions on the covariates, the resulting estimators are consistent and asymptotically normal. The analysis is applied to rainfall data where the goodness of fit is judged by a certain chi square statistic.en_US
dc.format.extent628336 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/5668
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 1995-86en_US
dc.subjectestimationen_US
dc.subjectsignal processingen_US
dc.subjectstatisticalen_US
dc.subjectregressionen_US
dc.subjecttime dependent coveriatesen_US
dc.subjectordinalen_US
dc.subjectautoregressionen_US
dc.subjectnonstationary,en_US
dc.titlePartial Likelihood Analysis of Categorical Time Series Modelsen_US
dc.typeTechnical Reporten_US

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