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- Title
Nonparametric detection of correlated errors.
- Authors
Tae Yoon Kim; Donghoh Kim; Byeong U. Park; Simpson, Douglas G.
- Abstract
In regression problems it is hard to detect correlated errors since the errors are not observed. In this paper, a nonparametric method is proposed for the detection of correlated errors when the design points are equally spaced. It turns out that the first‐order sample autocovariance of the residuals from the kernel regression estimates provides essential information about correlated errors and its bootstrap is quite effective in implementing such information.
- Subjects
STATISTICAL bootstrapping; BANDWIDTHS; REGRESSION analysis; NONPARAMETRIC signal detection; KERNEL functions
- Publication
Biometrika, 2004, Vol 91, Issue 2, p491
- ISSN
0006-3444
- Publication type
Article
- DOI
10.1093/biomet/91.2.491