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Matrix analysis of identifiability of some finite markov models

dc.contributor.authorMerryman, Coleman T.en_US
dc.contributor.authorGreeno, James G.en_US
dc.contributor.authorMillward, Richard B.en_US
dc.date.accessioned2006-09-11T16:24:05Z
dc.date.available2006-09-11T16:24:05Z
dc.date.issued1971-12en_US
dc.identifier.citationGreeno, James G.; Millward, Richard B.; Merryman, Coleman T.; (1971). "Matrix analysis of identifiability of some finite markov models." Psychometrika 36(4): 389-408. <http://hdl.handle.net/2027.42/45730>en_US
dc.identifier.issn1860-0980en_US
dc.identifier.issn0033-3123en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/45730
dc.description.abstractMethods developed by Bernbach [1966] and Millward [1969] permit increased generality in analyses of identifiability. Matrix equations are presented that solve part of the identifiability problem for a class of Markov models. Results of several earlier analyses are shown to involve special cases of the equations developed here. And it is shown that a general four-state chain has the same parameter space as an all-or-none model if and only if its representation with an observable absorbing state is lumpable into a Markov chain with three states.en_US
dc.format.extent1017113 bytes
dc.format.extent3115 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherSpringer-Verlag; Psychometric Societyen_US
dc.subject.otherAssessment, Testing and Evaluationen_US
dc.subject.otherPsychologyen_US
dc.subject.otherPsychometricsen_US
dc.subject.otherStatistical Theory and Methodsen_US
dc.subject.otherStatistics for Social Science, Behavorial Science, Education, Public Policy, and Lawen_US
dc.titleMatrix analysis of identifiability of some finite markov modelsen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelPsychologyen_US
dc.subject.hlbtoplevelSocial Sciencesen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumThe University of Michigan, USAen_US
dc.contributor.affiliationotherBrown University, USAen_US
dc.contributor.affiliationotherIndiana University, USAen_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/45730/1/11336_2005_Article_BF02291365.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1007/BF02291365en_US
dc.identifier.sourcePsychometrikaen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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