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Two procedures for robust monitoring of probability distributions of economic data stream induced by depth functions

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KOSIOROWSKI D.

Operations Research and Decisions

2015

vol. 25

issue 1

55-79

Data streams (streaming data) consist of transiently observed, evolving in time, multidimensional data sequences that challenge our computational and/or inferential capabilities. We propose user friendly approaches for robust monitoring of selected properties of unconditional and conditional distributions of the stream based on depth functions. Our proposals are robust to a small fraction of outliers and/or inliers, but at the same time are sensitive to a regime change in the stream. Their implementations are available in our free R package DepthProc

Głębia położenia-rozrzutu w strumieniowej analizie danych ekonomicznych

75%

Kosiorowski D.

Przegląd Statystyczny

2012

vol. 59

issue numer specjalny 1

87-108

In this paper we study the properties of the location-scale depth procedures introduced by Mizera & Müller and look into the probabilistic information of the underlying time series model carried by them. We focus our attention on short term multivariate quantile based description of the possible time series model. We study robustness and utility of such the description in a decision making process. In particular we investigate properties of the moving Student median (two dimensional Tukey median in a location–scale problem).

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1 Operations Research and Decisions

1 Przegląd Statystyczny

1 KOSIOROWSKI D.

1 Kosiorowski D.

1 2015

1 2012

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Two procedures for robust monitoring of probability distributions of economic data stream induced by depth functions

Głębia położenia-rozrzutu w strumieniowej analizie danych ekonomicznych