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On Local Smoothing of Nonparametric Curve Estimators
Jianqing Fan, Peter Hall, Michael A. Martin and Prakash Patil
Journal of the American Statistical Association
Vol. 91, No. 433 (Mar., 1996), pp. 258-266
Stable URL: http://www.jstor.org/stable/2291403
Page Count: 9
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We develop new local versions of familiar smoothing methods, such as cross-validation and smoothed cross-validation, in the contexts of density estimation and regression. These new methods are locally adaptive in the sense that they capture smooth local fluctuations in the curve by using smoothly varying bandwidths that change as the character of the curve changes. Moreover, the new methods are accurate, easy to apply, and computationally expedient.
Journal of the American Statistical Association © 1996 American Statistical Association