http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Applying maximum entropy to econometric problems
The entropy concept was developed and used by Shannon in 1940 as a measure of uncertainty in the context of information theory. In 1957 Jaynes made use of Shannon's entropy concept as a basis for estimation and inference in problems that are ill-suited for traditional statistical procedures. This volume consists of two sections. The first section contains papers developing econometric methods based on the entropy principle. An interesting array of applications is presented in the second section of the volume.
Information theoretic methods for categorical data : dedicated to the memory of Solomon Kullback 1907-1994 / D.V. Gokhale -- Model selection by maximum entropy / Jan G. De Gooijer -- Maximum-entropy acceptable-likelihood estimation of population heterogeneity / Peter S. Faynzilberg -- A monte carlo study of a generalized maximum entropy estimator of the binary choice model / Lee Adkins -- constructing a unimodal bayesian prior distribution from incompletely assessed information / Kwang H. Paick -- Recovering wastewater treatment objectives : an application of entropy estimation for inverse control problems / Linda Fernandez -- Dart boards and asset prices : Introducing the entropy pricing theory / Les Gulko -- Information theoretic regression methods : Dedicated to the memory of Solomon Kullback 1907-1994 / Ehsan S. Soofi -- Maximum entropy and derivative securities / Raymond J. Hawkins -- The maximum entropy approach to estimation and inference : an overview / Douglas Miller -- Forecasting the production benefits and incidence of a public program : an integrated survey and estimation procedure applied to study the california irrigation management information system / David Zilberman -- Another perspective on recent changes in the U.S. income distribution : an index space representation / Daniel J. Slottje -- Omnibus tests for multivariate normality based on a class of maximum entropy distributions / Carlos M. Urzua -- The Bayesian method of moments (BMOM) : theory and applications / Arnold Zellner.