文章基本信息

标题：A different perspective on the Propagation-Separation Approach
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作者：Saskia M. A. Becker ; Peter Mathé
期刊名称：Electronic Journal of Statistics
印刷版ISSN：1935-7524
出版年度：2013
卷号：7
页码：2702-2736
DOI：10.1214/13-EJS860
语种：English
出版社：Institute of Mathematical Statistics
摘要：The Propagation-Separation Approach is an iterative procedure for pointwise estimation of local constant and local polynomial functions. The estimator is defined as a weighted mean of the observations with data-driven, iteratively updated weights. Within homogeneous regions it ensures a similar behavior as non-adaptive smoothing (propagation), while avoiding smoothing among distinct regions (separation). In order to enable a proof of stability of estimates, the authors of the original study introduced an additional memory step aggregating the estimators of the successive iteration steps. Here, we study theoretical properties of the simplified algorithm, where the memory step is omitted. In particular, we introduce a new strategy for the choice of the adaptation parameter yielding propagation and stability for local constant functions with sharp discontinuities.
关键词：Structural adaptive smoothing;propagation, separation;local likelihood;exponential families.