preprint · RePEc: Research Papers in Economics

Global Polynomial Kernel Hazard Estimation.

Perch Nielsen, Jens, Tanggaard, Carsten

Cited by 0Abstract and details only

Abstract

This paper introduces a new bias reducing method for kernel hazard estimation. The method is called global polynomial adjustment (GPA). It is a global correction which is applicable to any kernel hazard estimator. The estimator works well from a theoretical point of view as it symptotically reduces bias with unchanged variance. A simulation study investigates the finite-sample properties of GPA. The method is tested on local constant and local linear estimators both with and without multiplicative bias correction and with the additive bias correction proposed in Nielsen and Tanggaard (2000). From the simulation experiment we conclude that the global estimator improves the goodness-of-fit. An especially encouraging result is that the bias-correction works well for small samples, where traditional bias reduction methods have a tendency to fail.

Cite this paper

APA 7

Perch Nielsen, J., & Tanggaard, C. (n.d.). Global Polynomial Kernel Hazard Estimation. RePEc: Research Papers in Economics.

MLA 9

Perch Nielsen, Jens, and Carsten Tanggaard. “Global Polynomial Kernel Hazard Estimation.” RePEc: Research Papers in Economics.

Chicago

Perch Nielsen, Jens, and Carsten Tanggaard. n.d.. “Global Polynomial Kernel Hazard Estimation.” RePEc: Research Papers in Economics.

Harvard

Perch Nielsen, J. and Tanggaard, C. (n.d.) ‘Global Polynomial Kernel Hazard Estimation’, RePEc: Research Papers in Economics.

BibTeX

@misc{perchnielsenglobal,
  title = {{Global Polynomial Kernel Hazard Estimation.}},
  author = {Perch Nielsen, Jens and Tanggaard, Carsten},
  journal = {RePEc: Research Papers in Economics}
}

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