Diagnostic testing and evaluation of maximum likelihood models
Abstract
The paper develops a unified theory of likelihood specification testing based on M-estimators
of auxiliary parameters. The theory is sufficiently general to encompass a wide class
of specification tests including moment-based tests, Pearson-type goodness of fit
tests, the information matrix test, and the Cox test. The paper also presents a framework
based on Frechet differentiation for determining the effects of misspecification on
the almost sure limits of parameter estimates and specification test statistics. ©
1985.
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https://hdl.handle.net/10161/1912Published Version (Please cite this version)
10.1016/0304-4076(85)90149-6Publication Info
(1985). Diagnostic testing and evaluation of maximum likelihood models. Journal of Econometrics, 30(1-2). pp. 415-443. 10.1016/0304-4076(85)90149-6. Retrieved from https://hdl.handle.net/10161/1912.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
George E. Tauchen
William Henry Glasson Distinguished Professor of Economics
George Tauchen is the William Henry Glasson Professor of Economics and professor of
finance at the Fuqua School of Business. He joined the Duke faculty in 1977 after
receiving his Ph.D. from the University of Minnesota. He did his undergraduate work
at the University of Wisconsin. Professor Tauchen is a fellow of the Econometric Society,
the American Statistical Association, the Journal of Econometrics, and the Society
for Financial Econometrics (SoFie). He is also the 2003 Duke University Sc
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