Arbeitspapier
Bias in nearest-neighbor hazard estimation
In nonparametric curve estimation, the smoothing parameter is critical for performance. In order to estimate the hazard rate, we compare nearest neighbor selectors that minimize the quadratic, the Kullback-Leibler, and the uniform loss. These measures result in a rule of thumb, a cross-validation, and a plug-in selector. A Monte Carlo simulation within the three-parameter exponentiated Weibull distribution indicates that a counter-factual normal distribution, as an input to the selector, does provide a good rule of thumb. If bias is the main concern, minimizing the uniform loss yields the best results, but at the cost of very high variability. Cross-validation has a similar bias to the rule of thumb, but also with high variability.
- Sprache
-
Englisch
- Erschienen in
-
Series: Technical Report ; No. 2008,15
- Thema
-
hazard rate
kernel smoothing
bandwidth selection
nearest neighbor bandwidth
rule of thumb
plug-in
cross-validation
credit risk
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Weißbach, Rafael
Dette, Holger
- Ereignis
-
Veröffentlichung
- (wer)
-
Technische Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
- (wo)
-
Dortmund
- (wann)
-
2008
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:44 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Weißbach, Rafael
- Dette, Holger
- Technische Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
Entstanden
- 2008
Ähnliche Objekte (12)
Bias in nearest-neighbor hazard estimation
On robust and efficient designs for risk estimation in epidemiologic studies
Robust designs for series estimation
Discount curve estimation by monotonizing McCulloch Splines
A note on all-bias designs with applications in spline regression models
On the estimation of a monotone conditional variance in nonparametric regression
The asymptotic minimax risk for the estimation of constrained binomial and multinomial probabilities
Optimal designs for testing the functional form of a regression via nonparametric estimation techniques
Canonical moments, orthogonal polynomials with application to statistics
Strong approximation of eigenvalues of large dimensional Wishart matrices by roots of generalized Laguerre polynomials
A note on a specification test for time series models based on spectral density estimation
Spectral analysis and minimax estimation in non-standard random matrix models
Bias in nearest-neighbor hazard estimation
On robust and efficient designs for risk estimation in epidemiologic studies
Robust designs for series estimation
Discount curve estimation by monotonizing McCulloch Splines
A note on all-bias designs with applications in spline regression models
On the estimation of a monotone conditional variance in nonparametric regression
The asymptotic minimax risk for the estimation of constrained binomial and multinomial probabilities
Optimal designs for testing the functional form of a regression via nonparametric estimation techniques
Canonical moments, orthogonal polynomials with application to statistics
Strong approximation of eigenvalues of large dimensional Wishart matrices by roots of generalized Laguerre polynomials
A note on a specification test for time series models based on spectral density estimation
Spectral analysis and minimax estimation in non-standard random matrix models
Bias in nearest-neighbor hazard estimation
On robust and efficient designs for risk estimation in epidemiologic studies
Robust designs for series estimation
Discount curve estimation by monotonizing McCulloch Splines
A note on all-bias designs with applications in spline regression models
On the estimation of a monotone conditional variance in nonparametric regression
The asymptotic minimax risk for the estimation of constrained binomial and multinomial probabilities
Optimal designs for testing the functional form of a regression via nonparametric estimation techniques
Canonical moments, orthogonal polynomials with application to statistics
Strong approximation of eigenvalues of large dimensional Wishart matrices by roots of generalized Laguerre polynomials
A note on a specification test for time series models based on spectral density estimation