Arbeitspapier
Testing linearity of regression models with dependent errors by kernel based methods
In a recent paper Gonzalez Manteiga and Vilar Fernandez (1995) considered the problem of testing linearity of a regression under MA structure of the errors using a weighted L1-distance between a parametric and a nonparametric fit. They established asymptotic normality of the corresponding test statistic under the hypothesis and under local alternatives. In the present paper we extend these results and establish asymptotic normality of the statistic under fixed alternatives. This result is then used to prove that the optimal (with respect to uniform maximization of power) weight function in the test of Gonzalez Manteiga and Vilar Fernandez (1995) is given by the Lebesgue measure independently of the design density_ The paper also discusses several extensions of tests proposed by Azzalini and Bow_ man (1993) Zheng (1996) and Dette (1999) to the case of non-independent errors and compares these methods with the method of Gonzalez Manteiga and Vilar Fernandez (1995). It is demonstrated that among the kernel based methods the approach of the latter authors is the most efficient from an asymptotic point of view.
- Sprache
-
Englisch
- Erschienen in
-
Series: Technical Report ; No. 2000,40
- Thema
-
Test of linearity
nonparametric regression
moving average process
optimal weighted least squares
asymptotic relative efficiency
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Biedermann, Stefanie
Dette, Holger
- Ereignis
-
Veröffentlichung
- (wer)
-
Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
- (wo)
-
Dortmund
- (wann)
-
2000
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Biedermann, Stefanie
- Dette, Holger
- Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
Entstanden
- 2000
Ähnliche Objekte (12)
A note on estimating a monotone regression by combining kernel and density estimates
Optimal design in regression models with correlated errors
A comparative study of monotone nonparametric kernel estimates
Testing additivity by kernel based methods - what is a reasonable test?
Testing strict monotonicity in nonparametric regression
Exact optimal designs for weighted least squares analysis with correlated errors
A power comparison between nonparametric regression tests
Estimating a convex function in nonparametric regression
Optimal experimental designs for inverse quadratic regression models
Nonparametric comparison of regression curves - an empirical process approach
Testing for symmetric error distribution in nonparametric regression models
Optimal designs for estimating the slope of a regression
A note on estimating a monotone regression by combining kernel and density estimates
Optimal design in regression models with correlated errors
A comparative study of monotone nonparametric kernel estimates
Testing additivity by kernel based methods - what is a reasonable test?
Testing strict monotonicity in nonparametric regression
Exact optimal designs for weighted least squares analysis with correlated errors
A power comparison between nonparametric regression tests
Estimating a convex function in nonparametric regression
Optimal experimental designs for inverse quadratic regression models
Nonparametric comparison of regression curves - an empirical process approach
Testing for symmetric error distribution in nonparametric regression models
Optimal designs for estimating the slope of a regression
A note on estimating a monotone regression by combining kernel and density estimates
Optimal design in regression models with correlated errors
A comparative study of monotone nonparametric kernel estimates
Testing additivity by kernel based methods - what is a reasonable test?
Testing strict monotonicity in nonparametric regression
Exact optimal designs for weighted least squares analysis with correlated errors
A power comparison between nonparametric regression tests
Estimating a convex function in nonparametric regression
Optimal experimental designs for inverse quadratic regression models
Nonparametric comparison of regression curves - an empirical process approach
Testing for symmetric error distribution in nonparametric regression models