Control charts for multivariate spatial autoregressive models

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Autorschaft

  • Robert Garthoff
  • Philipp Otto

Externe Organisationen

  • Europa-Universität Viadrina Frankfurt (Oder)
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Seiten (von - bis)67-94
Seitenumfang28
FachzeitschriftAStA Advances in Statistical Analysis
Jahrgang101
Ausgabenummer1
Frühes Online-Datum26 Juli 2016
PublikationsstatusVeröffentlicht - Jan. 2017
Extern publiziertJa

Abstract

This paper deals with spatial detection of changes in model parameters of spatial autoregressive processes. The respective sequential testing problems are formulated. Moreover, we introduce characteristic quantities to monitor means or covariances of multivariate spatial autoregressive processes. Additionally, we also take into account the simultaneous surveillance of the mean vector and the covariance matrix. The aim is to apply control charts, important tools of sequential analysis, to these quantities. The considered control procedures are based on either cumulative sums or exponential smoothing. Further, we illustrate the methodology of statistical process control studying the spectrum of additive colors in a satellite photograph. Via simulation studies, the proposed control procedures are calibrated for a predefined average run length. In addition, we compare the performance of the control procedures considering the out-of-control situation. Eventually, the control charts are applied, and the signals of the different schemes are visualized. The final results are critically discussed.

ASJC Scopus Sachgebiete

Zitieren

Control charts for multivariate spatial autoregressive models. / Garthoff, Robert; Otto, Philipp.
in: AStA Advances in Statistical Analysis, Jahrgang 101, Nr. 1, 01.2017, S. 67-94.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Garthoff R, Otto P. Control charts for multivariate spatial autoregressive models. AStA Advances in Statistical Analysis. 2017 Jan;101(1):67-94. Epub 2016 Jul 26. doi: 10.1007/s10182-016-0276-x
Garthoff, Robert ; Otto, Philipp. / Control charts for multivariate spatial autoregressive models. in: AStA Advances in Statistical Analysis. 2017 ; Jahrgang 101, Nr. 1. S. 67-94.
Download
@article{41ff32f4bf524f0bb0d680ec387e090f,
title = "Control charts for multivariate spatial autoregressive models",
abstract = "This paper deals with spatial detection of changes in model parameters of spatial autoregressive processes. The respective sequential testing problems are formulated. Moreover, we introduce characteristic quantities to monitor means or covariances of multivariate spatial autoregressive processes. Additionally, we also take into account the simultaneous surveillance of the mean vector and the covariance matrix. The aim is to apply control charts, important tools of sequential analysis, to these quantities. The considered control procedures are based on either cumulative sums or exponential smoothing. Further, we illustrate the methodology of statistical process control studying the spectrum of additive colors in a satellite photograph. Via simulation studies, the proposed control procedures are calibrated for a predefined average run length. In addition, we compare the performance of the control procedures considering the out-of-control situation. Eventually, the control charts are applied, and the signals of the different schemes are visualized. The final results are critically discussed.",
keywords = "Multivariate CUSUM charts, Multivariate EWMA charts, Spatial autoregressive model",
author = "Robert Garthoff and Philipp Otto",
note = "Publisher Copyright: {\textcopyright} 2016, Springer-Verlag Berlin Heidelberg.",
year = "2017",
month = jan,
doi = "10.1007/s10182-016-0276-x",
language = "English",
volume = "101",
pages = "67--94",
journal = "AStA Advances in Statistical Analysis",
issn = "1863-8171",
publisher = "Physica-Verlag",
number = "1",

}

Download

TY - JOUR

T1 - Control charts for multivariate spatial autoregressive models

AU - Garthoff, Robert

AU - Otto, Philipp

N1 - Publisher Copyright: © 2016, Springer-Verlag Berlin Heidelberg.

PY - 2017/1

Y1 - 2017/1

N2 - This paper deals with spatial detection of changes in model parameters of spatial autoregressive processes. The respective sequential testing problems are formulated. Moreover, we introduce characteristic quantities to monitor means or covariances of multivariate spatial autoregressive processes. Additionally, we also take into account the simultaneous surveillance of the mean vector and the covariance matrix. The aim is to apply control charts, important tools of sequential analysis, to these quantities. The considered control procedures are based on either cumulative sums or exponential smoothing. Further, we illustrate the methodology of statistical process control studying the spectrum of additive colors in a satellite photograph. Via simulation studies, the proposed control procedures are calibrated for a predefined average run length. In addition, we compare the performance of the control procedures considering the out-of-control situation. Eventually, the control charts are applied, and the signals of the different schemes are visualized. The final results are critically discussed.

AB - This paper deals with spatial detection of changes in model parameters of spatial autoregressive processes. The respective sequential testing problems are formulated. Moreover, we introduce characteristic quantities to monitor means or covariances of multivariate spatial autoregressive processes. Additionally, we also take into account the simultaneous surveillance of the mean vector and the covariance matrix. The aim is to apply control charts, important tools of sequential analysis, to these quantities. The considered control procedures are based on either cumulative sums or exponential smoothing. Further, we illustrate the methodology of statistical process control studying the spectrum of additive colors in a satellite photograph. Via simulation studies, the proposed control procedures are calibrated for a predefined average run length. In addition, we compare the performance of the control procedures considering the out-of-control situation. Eventually, the control charts are applied, and the signals of the different schemes are visualized. The final results are critically discussed.

KW - Multivariate CUSUM charts

KW - Multivariate EWMA charts

KW - Spatial autoregressive model

UR - http://www.scopus.com/inward/record.url?scp=84979687763&partnerID=8YFLogxK

U2 - 10.1007/s10182-016-0276-x

DO - 10.1007/s10182-016-0276-x

M3 - Article

VL - 101

SP - 67

EP - 94

JO - AStA Advances in Statistical Analysis

JF - AStA Advances in Statistical Analysis

SN - 1863-8171

IS - 1

ER -