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We derive general distribution tests based on the method of Maximum Entropy density

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Author Info
Thanasis Stengos () (University of Guelph, Canada and The Rimini Centre for Economics Analysis, Rimini, Italy.)
Ximing Wu† () (Texas A&M University, USA and University of Guelph, Canada)

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Abstract

The proposed tests are derived from maximizing the differential entropy subject to moment constraints. By exploiting the equivalence between the Maximum Entropy and Maximum Likelihood estimates of the general exponential family, we can use the conventional Likelihood Ratio, Wald and Lagrange Multiplier testing principles in the maximum entropy framework. In particular we use the Lagrange Multiplier method to derive tests for normality and their asymptotic properties. Monte Carlo evidence suggests that the proposed tests have desirable small sample properties.

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File URL: http://www.rcfea.org/RePEc/pdf/wp24_07.pdf
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Publisher Info
Paper provided by Rimini Centre for Economic Analysis in its series Working Paper Series with number 24-07.

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Date of creation: Jul 2007
Date of revision: Jul 2007
Handle: RePEc:rim:rimwps:24-07

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Related research
Keywords: distribution test; maximum entropy; normality.;

Find related papers by JEL classification:
C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Econometric and Statistical Methods; Specific Distributions

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