OPTIMAL-DESIGN FOR ESTIMATION OF VARIANCE IN NONPARAMETRIC REGRESSION USING 1ST-ORDER DIFFERENCES

• 成果类型: Article
• 署名作者: CHAN, LY
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• 发表日期: 1991
• 页码: 926929
• 关键词: residual variance

摘要

In nonparametric regression, the variance of the response can be estimated by the sum of squares of differences of the observed response. In this paper we obtain the most efficient design for a general variance estimator defined by first order differences. It is found that for this estimator, in the majority of cases, a good approximation to the most efficient design is the uniform design. The least efficient designs are also discussed.