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作者：Davies, PL; Kovac, A
作者单位：University of Duisburg Essen
摘要：The paper considers the problem of nonparametric regression with emphasis on controlling the number of local extremes. Two methods, the run method and the taut-string multiresolution method, are introduced and analyzed on standard test beds. It is shown that the number and locations of local extreme values are consistently estimated. Rates of convergence are proved for both methods. The run method converges slowly but can withstand blocks as well as a high proportion of isolated outliers. The ...
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作者：Kent, JT; Tyler, DE
作者单位：University of Leeds; Rutgers University System; Rutgers University New Brunswick
摘要：Constrained M-estimates of multivariate location and scatter are found by finding the global minimum of an objective function subject to a constraint. They are related to redescending M-estimates of multivariate location and scatter since any stationary point of the objective function corresponds to such an M-estimate. Unfortunately, even for the population form of the estimator, that is, the constrained dl-functional, the objective function may have multiple stationary points. In this paper, ...
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作者：Dette, H; Neumeyer, N
作者单位：Ruhr University Bochum
摘要：In the problem of testing the equality of k regression curves from independent samples, we discuss three methods using nonparametric estimators of the regression function. The first test is based on a linear combination of estimators for the integrated variance function in the individual samples and in the combined sample. The second approach transfers the classical one-way analysis of variance to the situation of comparing nonparametric curves, while the third test compares the differences be...
