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

Thanasis Stengos () and Ximing Wu ()

Working Paper Series from Rimini Centre for Economic Analysis

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.

Keywords: distribution test; maximum entropy; normality. (search for similar items in EconPapers)
JEL-codes: C1 C12 C16 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
Date: 2007-07, Revised 2007-07

Downloads: (external link)
http://www.rcfea.org/RePEc/pdf/wp24_07.pdf

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:rim:rimwps:24-07

Access Statistics for this paper

More papers in Working Paper Series from Rimini Centre for Economic Analysis
Contact information at EDIRC.
Series data maintained by Francesco Billi ().