Presenter(s)
2009 Shannon Lecture
Jorma Rissanen (University of Tampere)
Abstract
Abstract: In this talk we give a common theory of estimation of real-valued parameters, their number, and even of their structure. The same theory includes also optimal estimation of intervals. Although no 鈥渢rue鈥 data generating distribution is assumed the theory may be viewed as an extension and generalization of the customary theory of estimation of real-valued parameters due to Fisher, Cramer, Rao, and others.
The central concept is estimation capacity, analogous to but different from Shannon鈥檚 channel capacity, which defines the estimator. It also defines a criterion for computing the estimates which amounts to an application of complete minimum description length principle. Theorems for mathematically defined optimality properties are given. No comparable theory - we think - is possible without basic information and coding theory.