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Uniform Strong Consistent Estimation of an Ifra Distribution Function

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  • Rojo, J.
  • Samaniego, F. J.

Abstract

Let 1n be an estimator of an IFRA survival function 1 and let A be such that 0 = 2, and k = 2 if and only if A is the median of F. As a consequence, if 1n represents the empirical survival function, or the Kaplan-Meier estimator, the estimator 1n inherits the strong and uniform convergence properties, as well as the optimal rates of convergence of the empirical survival function and Kaplan-Meier estimator respectively. Simulations show a substantial improvement in mean-squared error when comparing 1n to those IFRA estimators available in the literature. Under suitable conditions, asymptotic confidence intervals for 1(t0) are also provided.

Suggested Citation

  • Rojo, J. & Samaniego, F. J., 1994. "Uniform Strong Consistent Estimation of an Ifra Distribution Function," Journal of Multivariate Analysis, Elsevier, vol. 49(1), pages 150-163, April.
    • Handle: RePEc:eee:jmvana:v:49:y:1994:i:1:p:150-163
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    Cited by:

    1. Jiménez, Javier Rojo & Villa-Diharce, Enrique & Flores, Miguel, 2001. "Nonparametric Estimation of the Dependence Function in Bivariate Extreme Value Distributions," Journal of Multivariate Analysis, Elsevier, vol. 76(2), pages 159-191, February.

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