We study maximum likelihood estimation in log-linear models under conditional Poisson sampling schemes. We derive necessary and sufficient conditions for existence of the maximum likelihood estimator ...

We used the model proposed by Umbach and Weinberg (1997) to devise a hierarchical procedure using log-linear models to estimate genetic effects and the effects of gene–age interaction and to ...

When you perform log-linear model analysis, you can request weighted least-squares estimates, maximum likelihood estimates, or both. By default, PROC CATMOD calculates maximum likelihood estimates ...

Model the data as a log-linear model with (the Poisson variance function) and where Yij= number of epileptic seizures in interval j tij= length of interval j The correlations between the counts are ...

We study parameter estimation in linear Gaussian covariance models, which are p-dimensional Gaussian models with linear constraints on the covariance matrix. Maximum likelihood estimation for this ...