TITLE

THE DERIVATION OF GOODMAN'S MODEL FROM A CONTINUOUS STATIONARY MARKOV-PROCESS

AUTHOR(S)
Schmeikal, Bernd
PUB. DATE
September 1977
SOURCE
Quality & Quantity;Sep77, Vol. 11 Issue 3, p195
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
The article focuses on continuous Markov-process. There exist models of multivariate analysis in which it is assumed that data are generated by stochastic processes. In such models the scientist begins with the interpretation or "decomposition" of the transition-matrix, which governs the movement of the system. For processes, which are represented in the form of equation in the article, such decomposition has been worked out by researcher James S. Coleman. The latest version of the model was presented in 1969. It allows for an optimization-procedure in a strictly normed, orthogonal space of probability-vectors. In his book Coleman tried to introduce multiplicative effects into the system. However, it turned out that such systems are solvable only in very restricted cases. Systems where additive and multiplicative effects are mixed cannot be normalized and can generally not be solved by some evident estimation-procedure. Until now researchers have done three things: they have transformed process into the language of the odds; have obtained a decomposition of equilibrium-odds into gamma-factors; and from this researchers got a linear decomposition of the log-odds.
ACCESSION #
9970549

 

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