Accession Number:

ADP007134

Title:

On 'Fit the Short Curve' Principle for Smoothing Nonparametric Estimators,

Descriptive Note:

Corporate Author:

TEXAS UNIV AT EL PASO DEPT OF MATHEMATICAL SCIENCES

Personal Author(s):

• Kozek, Andrzej S.
• Schuster, Eugene F.

Report Date:

1992-01-01

Pagination or Media Count:

4.0

Abstract:

Let X, Y be a bivariate random vector with EY oo. The nonparametric regression problem is to estimate the regression function rx EYX x 1 based on a random sample Xi, Yi, il,..,n from X, Y. The Nadaraya-Watson NW, the Nearest Neighbor NN, and the Optimal Quantile OQ kernel type estimators of rx defined in 2-4 depend on smoothing parameters h, k and p, respectively. The asymptotic optimal form of these smoothing parameters is known, see Coulomb 1977 and Mack 1981.

Descriptors:

• *STATISTICS
• ESTIMATES
• FUNCTIONS
• PARAMETERS
• BIVARIATE ANALYSIS
• PARAMETRIC ANALYSIS

Subject Categories:

• Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE