Derivation of Learning Process Statistics for a General Markov Model
- 1 June 1966
- journal article
- Published by Cambridge University Press (CUP) in Psychometrika
- Vol. 31 (2) , 225-234
- https://doi.org/10.1007/bf02289509
Abstract
A Markov learning model may be stated in the form of a transition matrix, starting vector, and response probability vector. Utilizing these and some general properties of absorbing Markov chains, general expressions are derived for several statistics of the learning process which can be applied to any model of this form. Included are derivations for the mean learning curve, number of total errors, trial numbers of the first success and the last error, and the number of error runs. As an illustration, all derivations are worked out for the simple two-state one-element model.Keywords
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