Afrika Statistika

Asymptotic Confidence Bands for Density and Regression Functions in the Gaussian Case

Nahima Nemouchi and Zaher Mohdeb

Full-text: Open access

Abstract

In this paper, we obtain asymptotic confidence bands for both the density and regression functions in the framework of nonparametric estimation. Beforehand, the asymptotic behaviors in probability of the kernel estimator of the density and the Nadaraya-Watson estimator of the regression function are described while local and global optimal smoothing parameters are investigated. A simulation study is conducted, showing the good performance of the confidence bands obtained for small sample.

Article information

Source
Afr. Stat., Volume 5, Number 1 (2010), 279-287.

Dates
First available in Project Euclid: 1 January 2014

Permanent link to this document
https://projecteuclid.org/euclid.as/1388545350

Mathematical Reviews number (MathSciNet)
MR2920305

Zentralblatt MATH identifier
1327.62222

Subjects
Primary: 62F35: Robustness and adaptive procedures 62G20: Asymptotic properties 62F15: Bayesian inference

Keywords
Confidence bounds Density estimation Kernel estimation Nonparametric estimation Regression estimation

Citation

Nemouchi, Nahima; Mohdeb, Zaher. Asymptotic Confidence Bands for Density and Regression Functions in the Gaussian Case. Afr. Stat. 5 (2010), no. 1, 279--287. https://projecteuclid.org/euclid.as/1388545350


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