The EM algorithm maximizes the expected log likelihood function given the current parameter estimates. In practice, the log likelihood function of the normal SSM is evaluated while the parameters are ...

Programming the EM algorithm developed in the study is made straightforward by following the EM steps described earlier. However, users can download the SAS/IML code that we used to analyze the ...

A. P. Dawid, A. M. Skene, Maximum Likelihood Estimation of Observer Error-Rates Using the EM Algorithm, Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 28, No. 1 (1979), ...

We consider novel methods for the computation of model selection criteria in missing-data problems based on the output of the EM algorithm. The methodology is very general and can be applied to ...