Arbeitspapier

Nonparametric significance testing

to connected objects

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).

Language: Englisch

Bibliographic citation: Series: SFB 373 Discussion Paper ; No. 1998,75

Classification: Wirtschaft
Model Evaluation, Validation, and Selection
Semiparametric and Nonparametric Methods: General

Subject: Hypothesis testing
Kernel estimation
Nested models

Event: Geistige Schöpfung

(who): Lavergne, Pascal
Vuong, Quang

Event: Veröffentlichung

(who): Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes

(where): Berlin

(when): 1998

Handle: http://hdl.handle.net/10419/61304

URN: urn:nbn:de:kobv:11-10060522

Last update: 10.03.2025, 11:44 AM CET

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Object type

Arbeitspapier

Associated

Lavergne, Pascal
Vuong, Quang
Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes

Time of origin

1998

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