Hiabu, M., Miranda, M. D. M., Nielsen, J. P., Spreeuw, J., Tanggaard, C. & Villegas, A. (2015). Global Polynomial Kernel Hazard Estimation. Revista Colombiana de Estadística, 38(2), pp. 399-411. doi: 10.15446/rce.v38n2.51668
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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 asymptotically 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. 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.
|Uncontrolled Keywords:||Kernel estimation; hazard function; local linear estimation; boundary kernels; polynomial correction.|
|Subjects:||H Social Sciences > HG Finance|
|Divisions:||Cass Business School > Faculty of Actuarial Science & Insurance|
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