Arbeitspapier

Optimal designs for estimating individual coefficients in Fourier regression models

to related objects

In the common trigonometric regression model we investigate the optimal design problem for the estimation of the individual coefficients, where the explanatory variable varies in the interval [-a ,a] ; 0 < a < t. It is demonstrated that the structure of the optimal design depends sensitively on the size of the design space. For many cases optimal designs can be found explicitly, where the complexity of the solution depends on the value of the parameter a and the order of the term, for which the corresponding coefficient has to be estimated.

Language: Englisch

Bibliographic citation: Series: Technical Report ; No. 2001,05

Subject: trigonometric regression
c-optimality
optimal design for estimating individual coefficients
Chebyshev approximation problem
implicit function theorem

Event: Geistige Schöpfung

(who): Dette, Holger
Melas, Viatcheslav B.

Event: Veröffentlichung

(who): Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen

(where): Dortmund

(when): 2001

Handle: http://hdl.handle.net/10419/77157

Last update: 10.03.2025, 11:42 AM CET

Data provider

This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.

Show original at data provider

Object type

Arbeitspapier

Associated

Dette, Holger
Melas, Viatcheslav B.
Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen

Time of origin

2001

Other Objects (12)

Optimal designs for estimating pairs of coefficients in Fourier regression models

Arbeitspapier

Optimal designs for estimating pairs of coefficients in Fourier regression models

Optimal designs for estimating individual coefficients in Fourier regression models and figures figure 1, figure 2, figure 3 and figure 4

Optimal designs for estimating individual coefficients in Fourier regression models and figures figure 1, figure 2, figure 3 and figure 4

Optimal designs for estimating individual coefficients in polynomial regression: A functional approach

Arbeitspapier

Optimal designs for estimating individual coefficients in polynomial regression: A functional approach

Estimating a convex function in nonparametric regression

Arbeitspapier

Estimating a convex function in nonparametric regression

Optimal designs for estimating the coefficients of the lower frequencies in trigonometric regression models

Arbeitspapier

Optimal designs for estimating the coefficients of the lower frequencies in trigonometric regression models

Optimal designs for estimating individual coefficients in polynomial regression - a functional approach and figures

Optimal designs for estimating individual coefficients in polynomial regression - a functional approach and figures

Optimal designs for estimating the slope of a regression

Arbeitspapier

Optimal designs for estimating the slope of a regression

E-optimal designs in Fourier regression models on a partial circle

Arbeitspapier

E-optimal designs in Fourier regression models on a partial circle

A note on estimating a monotone regression by combining kernel and density estimates

Arbeitspapier

A note on estimating a monotone regression by combining kernel and density estimates

Constrained optimal discriminating designs for Fourier regression models

Arbeitspapier

Constrained optimal discriminating designs for Fourier regression models

Testing strict monotonicity in nonparametric regression

Arbeitspapier

Testing strict monotonicity in nonparametric regression

A power comparison between nonparametric regression tests

Arbeitspapier

A power comparison between nonparametric regression tests

Optimal designs for estimating pairs of coefficients in Fourier regression models

Arbeitspapier

Optimal designs for estimating pairs of coefficients in Fourier regression models

Optimal designs for estimating individual coefficients in Fourier regression models and figures figure 1, figure 2, figure 3 and figure 4

Optimal designs for estimating individual coefficients in Fourier regression models and figures figure 1, figure 2, figure 3 and figure 4

Optimal designs for estimating individual coefficients in polynomial regression: A functional approach

Arbeitspapier

Optimal designs for estimating individual coefficients in polynomial regression: A functional approach

Estimating a convex function in nonparametric regression

Arbeitspapier

Estimating a convex function in nonparametric regression

Optimal designs for estimating the coefficients of the lower frequencies in trigonometric regression models

Arbeitspapier

Optimal designs for estimating the coefficients of the lower frequencies in trigonometric regression models

Optimal designs for estimating individual coefficients in polynomial regression - a functional approach and figures

Optimal designs for estimating individual coefficients in polynomial regression - a functional approach and figures

Optimal designs for estimating the slope of a regression

Arbeitspapier

Optimal designs for estimating the slope of a regression

E-optimal designs in Fourier regression models on a partial circle

Arbeitspapier

E-optimal designs in Fourier regression models on a partial circle

A note on estimating a monotone regression by combining kernel and density estimates

Arbeitspapier

A note on estimating a monotone regression by combining kernel and density estimates

Constrained optimal discriminating designs for Fourier regression models

Arbeitspapier

Constrained optimal discriminating designs for Fourier regression models

Testing strict monotonicity in nonparametric regression

Arbeitspapier

Testing strict monotonicity in nonparametric regression

A power comparison between nonparametric regression tests

Arbeitspapier

A power comparison between nonparametric regression tests

Optimal designs for estimating pairs of coefficients in Fourier regression models

Arbeitspapier

Optimal designs for estimating pairs of coefficients in Fourier regression models

Optimal designs for estimating individual coefficients in Fourier regression models and figures figure 1, figure 2, figure 3 and figure 4

Optimal designs for estimating individual coefficients in Fourier regression models and figures figure 1, figure 2, figure 3 and figure 4

Optimal designs for estimating individual coefficients in polynomial regression: A functional approach

Arbeitspapier

Optimal designs for estimating individual coefficients in polynomial regression: A functional approach

Estimating a convex function in nonparametric regression

Arbeitspapier

Estimating a convex function in nonparametric regression

Optimal designs for estimating the coefficients of the lower frequencies in trigonometric regression models

Arbeitspapier

Optimal designs for estimating the coefficients of the lower frequencies in trigonometric regression models

Optimal designs for estimating individual coefficients in polynomial regression - a functional approach and figures

Optimal designs for estimating individual coefficients in polynomial regression - a functional approach and figures

Optimal designs for estimating the slope of a regression

Arbeitspapier

Optimal designs for estimating the slope of a regression

E-optimal designs in Fourier regression models on a partial circle

Arbeitspapier

E-optimal designs in Fourier regression models on a partial circle

A note on estimating a monotone regression by combining kernel and density estimates

Arbeitspapier

A note on estimating a monotone regression by combining kernel and density estimates

Constrained optimal discriminating designs for Fourier regression models

Arbeitspapier

Constrained optimal discriminating designs for Fourier regression models

Testing strict monotonicity in nonparametric regression

Arbeitspapier

Testing strict monotonicity in nonparametric regression

A power comparison between nonparametric regression tests

Arbeitspapier

A power comparison between nonparametric regression tests

Cultural heritage institutions wishing to register will find more information here.

Fields marked * need to be filled in.

Username*

Please enter your username

Email*

Please enter your email address

Please do not fill this field

First name

Last name

Password*

Please enter your password

Confirm password*

Please enter the same password

I have read the terms of use and the privacy policy for the collection of personal data and accept them. *

This field is required.

I would like to subscribe to the newsletter of the Deutsche Digitale Bibliothek. See newsletter subscription info.

Account created

Your "My DDB" account has been successfully created. Before you can log in to your account, you must click the confirmation link in the message we just sent to the email address you provided.