Functional outlier detection by a local depth with application to NO x levels
نویسندگان
چکیده
منابع مشابه
Local Outlier Detection with Interpretation
Outlier detection aims at searching for a small set of objects that are inconsistent or considerably deviating from other objects in a dataset. Existing research focuses on outlier identification while omitting the equally important problem of outlier interpretation. This paper presents a novel method named LODI to address both problems at the same time. In LODI, we develop an approach that exp...
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Statistical depth functions provide from the “deepest” point a “centeroutward ordering” of multi-dimensional data. In this sense, depth functions can measure the “extremeness” or “outlyingness” of a data point with respect to a given data set. Hence they can detect outliers – observations that appear extreme relative to the rest of the observations. Of the various statistical depths, the spatia...
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Functional data are occurring more and more often in practice, and various statistical techniques have been developed to analyze them. In this paper we consider multivariate functional data, where for each curve and each time point a p-dimensional vector of measurements is observed. For functional data the study of outlier detection has started only recently, and was mostly limited to univariat...
متن کاملRejoinder to 'multivariate functional outlier detection'
First of all we would like to thank the editor, Professor Andrea Cerioli, for inviting us to submit our work and for requesting comments from some esteemed colleagues. We were surprised by the number of invited comments and grateful to their contributing authors, all of whom raised important points and/or offered valuable suggestions. We are happy for the opportunity to rejoin the discussion. R...
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A procedure for detecting outliers in regression problems is proposed. It is based on information provided by boosting regression trees. The key idea is to select the most frequently resampled observation along the boosting iterations and reiterate after removing it. The selection criterion is based on Tchebychev’s inequality applied to the maximum over the boosting iterations of ...
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ژورنال
عنوان ژورنال: Stochastic Environmental Research and Risk Assessment
سال: 2015
ISSN: 1436-3240,1436-3259
DOI: 10.1007/s00477-015-1096-3