Abstract
ABSTRACTThe theory of log‐linear models is developed for multinomially distributed data – i.e., frequency distributions and discrete multivariate distributions. Such models have applications to data smoothing and can be used in test equating. Attention is given to the computations used to find maximum likelihood estimates using Newton's method and to the computation of asymptotic standard errors for the fitted frequencies. Two examples, using real data, are used to illustrate the output of a computer program that implements these ideas.
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