Maximum Likelihood Methods for Log-Linear Models When Expected Frequencies are Subject to Linear Constraints

Hypotheses relating to log-linear models may be defined in terms of constraints on the frequencies or on the logarithms of the frequencies. A two-step algorithm is developed to allow fitting models containing constraints of both types. This algorithm is shown to yield maximum likelihood estimates of the log-linear parameters. Three examples are presented to illustrate cases in which these models are of interest.