๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Analysis of Variance in Nonparametric Regression Models

โœ Scribed by Holger Dette; Stephan Derbort


Publisher
Elsevier Science
Year
2001
Tongue
English
Weight
283 KB
Volume
76
Category
Article
ISSN
0047-259X

No coin nor oath required. For personal study only.

โœฆ Synopsis


In a nonparametric regression model with a multivariate explanatory variable we consider the problem of testing the hypothesis that specific interactions in a canonical decomposition of the model vanish. A simple consistent test is developed which is based on the difference between the corresponding sum of squares of the ordinary ANOVA for the multi-factor case and a nonparametric variance estimator. This presents an analogue of the classical ANOVA in the nonparametric regression setup. Asymptotic normality of the introduced test statistic is derived under the null hypothesis and under fixed alternatives. The finite sample behaviour of the proposed procedures is illustrated by a small simulation study and a data example. 2000


๐Ÿ“œ SIMILAR VOLUMES


Model Specification Tests in Nonparametr
โœ Jiti Gao; Howell Tong; Rodney Wolff ๐Ÿ“‚ Article ๐Ÿ“… 2002 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 235 KB

In this paper, we consider testing for additivity in a class of nonparametric stochastic regression models. Two test statistics are constructed and their asymptotic distributions are established. We also conduct a small sample study for one of the test statistics through a simulated example.

Variance regression models in experiment
โœ P. A. Barbetta; J. L. D. Ribeiro; R. W. Samohyl ๐Ÿ“‚ Article ๐Ÿ“… 2000 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 168 KB ๐Ÿ‘ 1 views

Variance models are highly important in developing robust products and processes. These models can be employed in process robustness studies through the use of response surface methodology. In most of the applications the models are constructed in terms of the logarithm of the sample variance or the