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.
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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.
- 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.
- del Rio, Alejandro Quintela, 1996. "Comparison of bandwidth selectors in nonparametric regression under dependence," Computational Statistics & Data Analysis, Elsevier, vol. 21(5), pages 563-580, May.
- 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.
- Cox, Dennis D. & Kim, Tae Yoon, 1995. "Moment bounds for mixing random variables useful in nonparametric function estimation," Stochastic Processes and their Applications, Elsevier, vol. 56(1), pages 151-158, March.
- Kim, Tae Yoon & Cox, Denis D., 1997. "A Study on Bandwidth Selection in Density Estimation under Dependence," Journal of Multivariate Analysis, Elsevier, vol. 62(2), pages 190-203, August.
- Kim, T. Y. & Cox, D. D., 1995. "Asymptotic Behaviors of Some Measures of Accuracy in Nonparametric Curve Estimation with Dependent Observations," Journal of Multivariate Analysis, Elsevier, vol. 53(1), pages 67-93, April.
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