Non-parametric estimation of conditional quantiles

M. Samanta

Statistics & Probability Letters, 1989, vol. 7, issue 5, 407-412

Abstract: Let (X, Y) be a two dimensional random variable with a joint density function f(x, y) and a joint distribution function F(x, y) = [small esh]x-[infinity][small esh]y-[infinity]f(u, v) dv du. Following Nadaraya (1964) and Rosenblatt (1969) a class of nonparametric estimators of conditional quantiles of Y for a given value of X, based on a random sample from the above distribution, is proposed. It is shown that under some regularity conditions the estimators are strongly consistent and asymptotically normally distributed.

Keywords: Quantile; regression; kernel; estimation; large; sample; methods (search for similar items in EconPapers)
Date: 1989
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Citations: View citations in EconPapers (18)

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