6533b7d8fe1ef96bd12697e8
RESEARCH PRODUCT
An approximation to maximum likelihood estimates in reduced models
David CoxNanny Wermuthsubject
Statistics and ProbabilityRestricted maximum likelihoodApplied MathematicsGeneral MathematicsMaximum likelihoodMultivariate normal distributionMaximum likelihood sequence estimationCovarianceAgricultural and Biological Sciences (miscellaneous)Extended modelStatisticsExpectation–maximization algorithmLog-linear modelStatistics Probability and UncertaintyGeneral Agricultural and Biological SciencesMathematicsdescription
SUMMARY An approximation to the maximum likelihood estimates of the parameters in a model can be obtained from the corresponding estimates and information matrices in an extended model, i.e. a model with additional parameters. The approximation is close provided that the data are consistent with the first model. Applications are described to log linear models for discrete data, to models for multivariate normal distributions with special covariance matrices and to mixed discrete-continuous models.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 1990-01-01 | Biometrika |