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 ...

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 ...

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 ...

Log-normal linear regression models are popular in many fields of research. Bayesian estimation of the conditional mean of the dependent variable is problematic as many choices of the prior for the ...

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 ...