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Matrix Analysis of Identifiability of Some Finite Markov Models

Published online by Cambridge University Press:  01 January 2025

James G. Greeno ,
Richard B. Millward  and
Coleman T. Merryman
James G. Greeno
Affiliation:
The University of Michigan
Richard B. Millward
Affiliation:
Brown University
Coleman T. Merryman
Affiliation:
Indiana University
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Abstract

Methods 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.

Type
Original Paper
Information
Psychometrika , Volume 36 , Issue 4 , December 1971 , pp. 389 - 408
Copyright
Copyright © 1971 The Psychometric Society

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Footnotes

*

This research was supported by the U.S. Public Health Service under Grant MH-12717 to Indiana University and Grant GM-1231 to the University of Michigan.

†

Now at the University of Texas, Austin.

References

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