Algorithm AS 253: Maximum Likelihood Estimation of the RC(M) Association Model
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TL;DR
The subroutine RCM fits the RC(M) association model (Goodman) to a given two-way cross-classification of counts based on the cyclic application of Newton's elementary (univariate) method.
Abstract
The subroutine RCM fits the RC(M) association model (Goodman) to a given two-way cross-classification of counts. The algorithm is based on the cyclic application of Newton's elementary (univariate) method. The user is provided with the option of specifying: (a) the dimension of the model, say M, (b) the weight vectors used to identify the association parameters (row and column scores) and (c) cells to be «banked out» (e.g. structural zeros)