Testing the Hypothesis of a Homoscedastic Error Term in Simple, Nonparametric Regression  

Oleh:

Wilcox, Rand R.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Educational and Psychological Measurement vol. 66 no. 01 (Feb. 2006), page 85-92.
Topik: heteroscedasticity; smoothers; Theil-Sen estimator; Winsorized correlations
Fulltext: 85.pdf (78.9KB)

Isi artikel

(PKPM) Consider the nonparametric regression model Y = m(X) + t(X)e, where X and e are independent random variables, e has a median of zero and variance s2, t is some unknown function used to model heteroscedasticity, and m(X) is an unknown function reflecting some conditional measure of location associated with Y, given X. This article considers the problem of testing H0:t = 1, the hypothesis that the error term is homoscedastic. Several methods were considered, two of which were found that control the probability of a Type I error well in simulations. One is fast from a computational point of view, and the other is based in part on a bootstrap method. Neither dominates in terms of power.

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