Nonparametric Significance Testing
dc.contributor.author | Lavergne, Pascal | |
dc.contributor.author | Vuong, Quang | |
dc.date.accessioned | 2017-06-15T22:02:18Z | |
dc.date.available | 2017-06-15T22:02:18Z | |
dc.date.created | 2006-03-15 | |
dc.date.issued | 1998-06-01 | |
dc.identifier.issn | 1436-1086 | |
dc.identifier.uri | http://edoc.hu-berlin.de/18452/4413 | |
dc.description.abstract | A procedure for testing the signicance of a subset of explanatory variables in a nonparametric regression is proposed. Our test statistic uses the kernel method. Under the null hypothesis of no effect of the variables under test, we show that our test statistic has a nhp2/2 standard normal limiting distribution, where p2 is the dimension of the complete set of regressors. Our test is one-sided, consistent against all alternatives and detect local alternatives approaching the null at rate slower than n-1/2 h-p2/4. Our Monte-Carlo experiments indicate that it outperforms the test proposed by Fan and Li (1996). | eng |
dc.language.iso | eng | |
dc.publisher | Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät | |
dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | |
dc.subject | Hypothesis testing | eng |
dc.subject | Kernel estimation | eng |
dc.subject | Nested models | eng |
dc.subject.ddc | 330 Wirtschaft | |
dc.title | Nonparametric Significance Testing | |
dc.type | book | |
dc.identifier.urn | urn:nbn:de:kobv:11-10060522 | |
dc.identifier.doi | http://dx.doi.org/10.18452/3761 | |
dc.subject.dnb | 17 Wirtschaft | |
local.edoc.pages | 30 | |
local.edoc.type-name | Buch | |
local.edoc.container-type | series | |
local.edoc.container-type-name | Schriftenreihe | |
local.edoc.container-year | 1998 | |
dc.identifier.zdb | 2135319-0 | |
bua.series.name | Sonderforschungsbereich 373: Quantification and Simulation of Economic Processes | |
bua.series.issuenumber | 1998,75 |