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2006-01-12Buch DOI: 10.18452/3678
Comparison of Nonparametric Goodness of Fit Tests
dc.contributor.authorLäuter, Henning
dc.contributor.authorSachsenweger, Cornelia
dc.date.accessioned2017-06-15T21:46:22Z
dc.date.available2017-06-15T21:46:22Z
dc.date.created2006-01-12
dc.date.issued2006-01-12
dc.identifier.issn1436-1086
dc.identifier.urihttp://edoc.hu-berlin.de/18452/4330
dc.description.abstractWe consider two tests for testing the hypothesis that a density lies in a parametric class of densities and compare them by means of simulation. Both considered tests are based on the integrated squared distance of the kernel density estimator from its hypothetical expectation. However, different kernels are used. The unknown parameter will be replaced by its maximum-likelihood-estimation (m.l.e.). The power of both tests will be examined under local alternatives. Although both tests are asymptotically equivalent, it will be shown that there is a difference between the power of both tests when a finite number of random variables is used. Furthermore it will be shown that asymptotically equivalent approximations of the power can differ significantly when finite sample sizes are used.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectsimulationeng
dc.subjectkernel estimatoreng
dc.subjectGoodness of fiteng
dc.subjectlocal alternativeseng
dc.subject.ddc330 Wirtschaft
dc.titleComparison of Nonparametric Goodness of Fit Tests
dc.typebook
dc.identifier.urnurn:nbn:de:kobv:11-10056006
dc.identifier.doihttp://dx.doi.org/10.18452/3678
dc.subject.dnb17 Wirtschaft
local.edoc.container-titleSonderforschungsbereich 373: Quantification and Simulation of Economic Processes
local.edoc.pages16
local.edoc.type-nameBuch
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-volume1999
local.edoc.container-issue2
local.edoc.container-year1999
local.edoc.container-erstkatid2135319-0

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