anomaly recognition has always been a prominent subject in preliminary geochemical explorations. among the regional geochemical data processing, there are a range of statistical and data mining techniques as well as different mapping methods, which serve as presentations of the outputs. the outlier’s values are of interest in the investigations where data are gathered under controlled condition...

Anomaly recognition has always been a prominent subject in preliminary geochemical explorations. Among the regional geochemical data processing, there are a range of statistical and data mining techniques as well as different mapping methods, which serve as presentations of the outputs. The outlier’s values are of interest in the investigations where data are gathered under controlled condition...

A spatial outlier is a spatially referenced object whose non-spatial attribute values are significantly different from the values of its neighborhood. Identification of spatial outliers can lead to the discovery of unexpected, interesting, and useful spatial patterns for further analysis. Previous work in spatial outlier detection focuses on detecting spatial outliers with a single attribute. I...

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...

in this paper a novel process monitoring scheme for reducing the type і and type іі error rates in the monitoring phase is proposed. first, the proposed approach uses an augmented data matrix to implement the process dynamic. then, we apply independent component analysis (ica) transformation to the augmented data matrix, and eliminate the outliers using the local outlier factor (lof) algorithm....