Recursive Estimation for Time Series Following Generalized Linear Models

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dc.contributor.authorFokianos, Konstantinosen_US
dc.contributor.authorKedem, Benjaminen_US
dc.contributor.departmentISRen_US
dc.date.accessioned2007-05-23T10:01:50Z
dc.date.available2007-05-23T10:01:50Z
dc.date.issued1996en_US
dc.description.abstractA recursive estimation method for time series models following generalized linear models is studied in two ways. The estimation procedure, suitably modified, gives rise to a stochastic approximation scheme. We use the modified estimation procedure to illustrate a connection between control theory and generalized linear models by employing a logistic regression model.en_US
dc.format.extent757980 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/5767
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 1996-48en_US
dc.subjectestimationen_US
dc.subjectadaptive controlen_US
dc.subjectoptimal control stochastic systemsen_US
dc.subjectlongitudinal dataen_US
dc.subjectstochastic approximationen_US
dc.subjectpartial likelihooden_US
dc.subjecttracking,en_US
dc.titleRecursive Estimation for Time Series Following Generalized Linear Modelsen_US
dc.typeTechnical Reporten_US

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