Nonparametric regression with errors in both variables : the Berkson model /

Bibliographic Details
Main Author:	Spiegelman, Clifford H. (Clifford Henry) (Author)
Format:	Book
Language:	English
Published:	College Station, Texas : Department of Statistics, Texas A & M University, [1989]
Series:	Technical report (Texas A & M University. Department of Statistics) ; no. 74.
Subjects:	Errors-in-variables models. Monte Carlo method. Error analysis (Mathematics) Nonparametric statistics. Regression analysis. Mathematical statistics. Statistics > Nonparametric inference > Nonparametric regression. Bias reduction

Description
Abstract:	Using Monte-Carlo experiments this paper shows that for the Berkson errors-in-variables model uncorrected smoothing can produce curves that are seriously biased. This paper gives a very simple and effective method for reducing this bias. The method uses the solution to an ordinary second order differential equation.
Physical Description:	14 leaves : illustrations ; 28 cm
Bibliography:	Includes bibliographical references (leaves 13-14).