Author： Mugdadi A. R.
Publisher： Taylor & Francis Ltd
ISSN： 1048-5252
Source： Journal of Nonparametric Statistics, Vol.17, Iss.7, 2005-10, pp. : 807-818
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Abstract
Let be identically and independently distributed (i.i.d.) observations on a random variable X with unknown distribution function F and density f . The kernel density estimate of the function was proposed by [Frees, E., 1994, Estimating densities of functions of observations. Journal of the American Statistical Association , 89, 517–525]. In this paper, we propose a kernel method to estimate the distribution function of the function and we derive the asymptotic mean-square error for the estimator. In addition, we propose two data-based methods to obtain the bandwidth.
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