A Distribution-free Multivariate Change-point Model for Statistical Process Control

Zhou, Maoyuan; Zi, Xuemin; Geng, Wei; Li, Zhonghua

doi:10.1080/03610918.2013.835411

Cited by 11 publications

(16 citation statements)

References 25 publications

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“…Qiu and Hawkins (2001), Qiu and Hawkins (2003), Hawkins and Deng (2010) developed change point models with assumed pre-knowledge in in-control distribution. Another part of research focusing on online nonparametric multivariate change point models can be found in Zou et al (2012), Holland and Hawkins (2014) and Zhou et al (2015). A special accumulation of recent papers on nonparametric control chart can be referred to Chakraborti et al (2015).…”

Section: Introductionmentioning

confidence: 99%

“…The simulation study investigates the ETCC in detecting mean and covariance shifts (in multivariate Gaussian, Student-t, Gamma and Laplace distributions). The performance of the ETCC was compared with the benchmark control charts including the spatial rank based EWMA (SREWMA) by Zou et al (2012), the self-starting multivariate minimal spanning tree (SMMST) based control chart by Zhou et al (2015) and the nonparametric multivariate change point (NPMVCP) model based control chart by Holland and Hawkins (2014). Results indicates a very good performance of the proposed chart.…”

Section: Introductionmentioning

confidence: 99%

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A comparison study of pricing credit default swap index tranches with convex combination of copulae

Okhrin

2017

The North American Journal of Economics and Finance

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This dissertation focuses on the high dimensional financial engineering, especially in dependence modeling and sequential surveillance.In aspect of dependence modeling, an introduction of high dimensional copula concentrating on state-of-the-art research in copula is presented. Factor copula, hierarchical Archimedean copula and vine copula are explicated, including their statistical inference.An empirical study in risk management by employing the introduced copulas is given.A more complex application in financial engineering using high dimensional copula is concentrated on the pricing of the portfolio-like credit derivative, i.e. credit default swap index (CDX) tranches. In this part, the convex combination of copulas is proposed in CDX tranche pricing with components stemming from elliptical copula family (Gaussian and Student-t), Archimedean copula family (Frank, Gumbel, Clayton and Joe) and hierarchical Archimedean copula family used in some publications. By comparison of two diverse credit derivatives, one can find that the convex combination of copulas has cutting edge in pricing CDX and CDO with components from Archimedean copula family with asymmetric tail dependence structures, e.g. Clayton, Gumbel and Joe copulas.In financial surveillance part, the chapter focuses on the monitoring of high dimensional portfolios (in 5, 29 and 90 dimensions) by development of a nonparametric multivariate statistical process control chart, i.e. energy test based control chart (ETCC). The main features in ETCC are in three aspects. Firstly, the ETCC is nonparametric control chart which means it requires no pre-knowledge on the processes compared to many traditional parametric control chart, e.g. CUSUM and EWMA. Secondly, ETCC monitors multivariate processes, which are more often in the real life. Since multivariate processes bring more characteristics than the unique process, hence ETCC has strong potential in many application areas. Thirdly and the most important virtue of the ETCC is that it monitors the mean and covariance jointly, not separately, compared to many other control charts. Since its powerful detection capacity in covariance change, hence it has good performance for financial sequences during crisis period, where volatility is the main trigger of shift.In order to support the further research and practice of nonparametric multivariate statistical process control chart devised in this dissertation, an R package "EnergyOnlineCPM" is developed. At moment, this package has been accepted and published in the Comprehensive R Archive Network (CRAN), which is the first package that can online monitor the shift in mean and covariance jointly.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A comparison study of pricing credit default swap index tranches with convex combination of copulae

Okhrin

2017

The North American Journal of Economics and Finance

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“…14,15 A nice overview on this topic of univariate nonparametric control charts was presented by Chakraborti et al 1 and Qiu. 16 Four important recent references on nonparametric control charts are Qiu and Zhang,17 McGinnity et al, 18 Chowdhury et al, 19 and Zhou et al 20 In addition, nonparametric control charts in multivariate cases have been discussed by Zhou et al 35 , Zhou et al 36 , among others.…”

Section: Introductionmentioning

confidence: 99%

“…and Qiu . Four important recent references on nonparametric control charts are Qiu and Zhang, McGinnity et al ., Chowdhury et al ., and Zhou et al . In addition, nonparametric control charts in multivariate cases have been discussed by Zhou et al ,.…”

Section: Introductionmentioning

confidence: 99%

A New Nonparametric Control Chart for Monitoring Variability

Zhou

Geng

2016

Quality & Reliability Eng

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Statistical process control is widely used in industrial processes, service fields, among others. While parametric control charts are useful in certain processes, there is often a lack of enough knowledge about the process distribution. So, nonparametric control charts are needed in such situations. This paper develops a new nonparametric control chart based on the AnsariBradley nonparametric test and the effective change point model. Simulation results show that our proposed control chart is superior to other nonparametric control charts in monitoring process variability for most cases. Our proposed control chart is easy in computation, and powerful for monitoring process variability.

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“…, Zou et al31 , Li32 , Cheng and Shiau 33 , Ou et al34 and Zou et al35 .Both data sets for the red and the white wine variants are available for research use in the UC Irvine Machine Learning Repository and downloadable at https://archive.ics.uci.edu/ml/datasets/Wine+Quality. The data were collected from May/2004 to February/2007…”

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confidence: 99%

A Bivariate Semiparametric Control Chart Based on Order Statistics

Koutras

Sofikitou

2016

Quality & Reliability Eng

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In this article, a new bivariate semiparametric Shewhart-type control chart is presented. The proposed chart is based on the bivariate statistic (X (r) , Y (s) ), where X (r) and Y (s) are the order statistics of the respective X and Y test samples. It is created by considering a straightforward generalization of the well-known univariate median control chart and can be easily applied because it calls for the computation of two single order statistics. The false alarm rate and the in-control run length are not affected by the marginal distributions of the monitored characteristics. However, its performance is typically affected by the dependence structure of the bivariate observations under study; therefore, the suggested chart may be characterized as a semiparametric control chart.An explicit expression for the operating characteristic function of the new control chart is obtained. Moreover, exact formulae are provided for the calculation of the alarm rate given that the characteristics under study follow specific bivariate distributions. In addition, tables and graphs are given for the implementation of the chart for some typical average run length values and false alarm rates. The performance of the suggested chart is compared with that of the traditional χ 2 chart as well as to the nonparametric SN 2 and SR 2 charts that are based on the multivariate form of the sign test and the Wilcoxon signed-rank test, respectively. Finally, in order to demonstrate the applicability of our chart, a case study regarding a realworld problem related to winery production is presented.

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A Distribution-free Multivariate Change-point Model for Statistical Process Control

Cited by 11 publications

References 25 publications

A comparison study of pricing credit default swap index tranches with convex combination of copulae

A comparison study of pricing credit default swap index tranches with convex combination of copulae

A New Nonparametric Control Chart for Monitoring Variability

A Bivariate Semiparametric Control Chart Based on Order Statistics

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