Maximum Likelihood Estimation of Functional Relationships

The theory of functional relationships concerns itself with inference from models which have a more complex error structure than simple regression models. In the natural and social sciences, there is considerable interest in considering such models since very often researchers are studying random variables related by mathematical formulae. The aim of this volume is to extend the theory of maximum likelihood estimators to functional relationships. Apart from exploring the theory itself, emphasis is also placed on the derivation of usefulestimators and discussing their second moment properties. Both full and conditional likelihood methods are considered and several numerical examples are presented to illustrate the theory.