Jump Detection in Regression Surfaces
Jump Detection in Regression Surfaces
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DOI：
10.1080/10618600.1997.10474746
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发表时间：
1997-09
影响因子：
2.4
通讯作者：
P. Qiu;B. Yandell
中科院分区：
文献类型：
--
作者：
P. Qiu;B. Yandell
摘要本文研究了回归曲面中跳跃点的定位问题。提出了一种基于局部最小二乘估计的跳变检测算法。这种方法需要O（Nk）的计算，其中N是样本大小，k是邻域的窗口宽度。此属性使处理大型数据集成为可能。对跳跃位置曲线、跳跃表面和噪声施加的条件是温和的。我们详细地证明了这种方法与一些数值例子。
Abstract We consider the problem of locating jumps in regression surfaces. A jump detection algorithm is suggested based on local least squares estimation. This method requires O(Nk) computations, where N is the sample size and k is the window width of the neighborhood. This property makes it possible to handle large data sets. The conditions imposed on the jump location curves, the jump surfaces, and the noise are mild. We demonstrate this method in detail with some numerical examples.