Statistical process monitoring of multivariate time-between-events data: Problems and possible solutions

Chenglong Li; Amitava Mukherjee; Qin Su; Min Xie

Statistical process monitoring of multivariate time-between-events data: Problems and possible solutions

Chenglong Li, Amitava Mukherjee, Qin Su, Min Xie

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

Abstract

In the recent years, a lot of attention is paid to univariate monitoring of time-between-events. When the univariate problem is extended to a multivariate situation, this study indicates that there is an emerging issue about the presence of asynchronous observations. This brings the new statistical challenge due to the way of data acquisition changes. This study also tries to give some possible solving ideas for the monitoring and analysis of multivariate TBE data stream.

Original language	English
Title of host publication	Intelligent Statistical Quality Control
Publisher	Helmut Schmidt University
Pages	245-250
Publication status	Published - 2016
Event	12th International Workshop on Intelligent Statistical Quality Control, IWISQC 2016 - Hamburg, Germany Duration: 16 Aug 2016 → 19 Aug 2016

Conference

Conference	12th International Workshop on Intelligent Statistical Quality Control, IWISQC 2016
Place	Germany
City	Hamburg
Period	16/08/16 → 19/08/16

Research Keywords

Asynchronous observation
Multivariate exponential distribution
Statistical process monitoring
Time-between-events

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title = "Statistical process monitoring of multivariate time-between-events data: Problems and possible solutions",

abstract = "In the recent years, a lot of attention is paid to univariate monitoring of time-between-events. When the univariate problem is extended to a multivariate situation, this study indicates that there is an emerging issue about the presence of asynchronous observations. This brings the new statistical challenge due to the way of data acquisition changes. This study also tries to give some possible solving ideas for the monitoring and analysis of multivariate TBE data stream.",

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author = "Chenglong Li and Amitava Mukherjee and Qin Su and Min Xie",

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pages = "245--250",

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note = "12th International Workshop on Intelligent Statistical Quality Control, IWISQC 2016 ; Conference date: 16-08-2016 Through 19-08-2016",

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Statistical process monitoring of multivariate time-between-events data: Problems and possible solutions. / Li, Chenglong; Mukherjee, Amitava; Su, Qin et al.
Intelligent Statistical Quality Control. Helmut Schmidt University, 2016. p. 245-250.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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AU - Mukherjee, Amitava

AU - Su, Qin

AU - Xie, Min

PY - 2016

Y1 - 2016

N2 - In the recent years, a lot of attention is paid to univariate monitoring of time-between-events. When the univariate problem is extended to a multivariate situation, this study indicates that there is an emerging issue about the presence of asynchronous observations. This brings the new statistical challenge due to the way of data acquisition changes. This study also tries to give some possible solving ideas for the monitoring and analysis of multivariate TBE data stream.

AB - In the recent years, a lot of attention is paid to univariate monitoring of time-between-events. When the univariate problem is extended to a multivariate situation, this study indicates that there is an emerging issue about the presence of asynchronous observations. This brings the new statistical challenge due to the way of data acquisition changes. This study also tries to give some possible solving ideas for the monitoring and analysis of multivariate TBE data stream.

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KW - Multivariate exponential distribution

KW - Statistical process monitoring

KW - Time-between-events

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M3 - RGC 32 - Refereed conference paper (with host publication)

SP - 245

EP - 250

BT - Intelligent Statistical Quality Control

PB - Helmut Schmidt University

Y2 - 16 August 2016 through 19 August 2016

ER -

Statistical process monitoring of multivariate time-between-events data: Problems and possible solutions

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Research Keywords

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