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Estimating Transition Probabilities from Aggregate Samples Augmented by Haphazard Recaptures

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Estimating Transition Probabilities from Aggregate Samples Augmented by Haphazard Recaptures

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dc.contributor.author Hawkins, D. L. en
dc.contributor.author Eisenfeld, Jerome en
dc.contributor.author Han, C. P. en
dc.date.accessioned 2010-06-14T16:43:46Z en
dc.date.available 2010-06-14T16:43:46Z en
dc.date.issued 1995 en
dc.identifier.uri http://hdl.handle.net/10106/2503 en
dc.description.abstract Transition probabilities provide a convenient summary of changes in a categorical trait over time in a population. The difficulties of estimating such probabilities based on only aggregate data from repeated sampling are well known. We give here a method for augmenting aggregate data with haphazard recapture data, which can dramatically improve the estimation precision of transition probabilities. The method requires a rather high sampling fraction to provide sufficient numbers of recaptures. It is based on a generalized nonlinear least squares strategy which yields transition probability estimates preserving their natural parameter space, and which are asymptotically efficient. The asymptotic theory is given under finite population sampling assumptions which are typical in practice. en
dc.language.iso en_US en
dc.publisher University of Texas at Arlington en
dc.relation.ispartofseries Technical Report;302 en
dc.subject Aggregate data en
dc.subject Sampling schemes en
dc.subject Recaptures en
dc.subject.lcsh Mathematics Research en
dc.subject.lcsh Statistics en
dc.title Estimating Transition Probabilities from Aggregate Samples Augmented by Haphazard Recaptures en
dc.type Technical Report en
dc.publisher.department Department of Mathematics en

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