On convergence rates for quadratic errors in kernel hazard estimation
Vieu (J. Multivariate Anal. 39 (1991) 324) showed that the quadratic errors for kernel estimates of several curves (including distribution and hazard functions) are asymptotically equivalent under strong mixing conditions. In this paper, the convergence rates of the distances between these quadratic errors are investigated in the particular case of the distribution and hazard functions.
Volume (Year): 57 (2002)
Issue (Month): 3 (April)
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- Vieu, Philippe, 1991. "Quadratic errors for nonparametric estimates under dependence," Journal of Multivariate Analysis, Elsevier, vol. 39(2), pages 324-347, November.
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- Hall, Peter, 1984. "Central limit theorem for integrated square error of multivariate nonparametric density estimators," Journal of Multivariate Analysis, Elsevier, vol. 14(1), pages 1-16, February.
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- Marron, James Stephen & Härdle, Wolfgang, 1986. "Random approximations to some measures of accuracy in nonparametric curve estimation," Journal of Multivariate Analysis, Elsevier, vol. 20(1), pages 91-113, October.
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