The efficiency of constructed bivariate copulas for MEWMA and Hotelling’s T2 control charts

Author(s):  
Sirasak Sasiwannapong ◽  
Saowanit Sukparungsee ◽  
Piyapatr Busababodhin ◽  
Yupaporn Areepong
2017 ◽  
Vol 14 (1) ◽  
pp. 1
Author(s):  
Hakan Eygü ◽  
M. Suphi Özçomak

The sample of the study was formed using simple random sampling, ranked set sampling, extreme ranked set sampling and median ranked set sampling. At the end of this process, the researcher created Hotelling’s T2 control charts, a multivariate statistical process control method. The performances of SRS, RSS, ERSS and MRSS sampling methods were compared to one another using these control charts. A simulation was performed to see the average run-length values for Hotelling’s T2 control charts, and these findings were also used for the comparison of the sampling performances.At the end of the study, the researcher formed a sample using median ranked set sampling and created the Hotelling’s T2 control chart. As a result of this operation, the researcher found that there was an out-of-control signal in the process, while there was no such signal in other sampling methods. When the average run-length values obtained from Hotelling’s T2 control charts were compared, it was seen that a shift in the process was detected by the ranked set sampling earlier, when compared to other sampling methods. This paper it can be said that the methods used are unique to the literature because they are applied to multivariate data.


2013 ◽  
Vol 63 (2) ◽  
Author(s):  
S. L. Lee ◽  
M. A. Djauhari

To monitor a multivariate process mean, Hotelling’s T2 control chart is often used. However, the presence of multiple outliers may go undetected due to the masking effect or swamping effect. In this study, we propose a robust Hotelling’s T2 control charts where the mean vector and the covariance matrix are estimated by using fast minimum covariance determinant (FMCD) which gives a high breakdown point estimates. This study found that the latter approach performs far better than the former in terms of the ability in detecting an out-of-control situation during the start-up stage. We present and discuss our experience in monitoring the process mean of cocoa powder production process in a Malaysian company located in Johor Bahru.


2010 ◽  
Vol 21 (05) ◽  
pp. 347-356 ◽  
Author(s):  
Lyndal Carter ◽  
Maryanne Golding ◽  
Harvey Dillon ◽  
John Seymour

Background: With the advent of newborn hearing screening programs, the need to verify the fit of hearing aids in young infants has increased. The recording of cortical auditory evoked potentials (CAEPs) for this purpose is quite feasible, but rapid developmental changes that affect response morphology and the presence of electrophysiological noise can make subjective response detection challenging. Purpose: The purpose of this study was to investigate the effectiveness of an automated statistic versus experienced examiners in detecting the presence of infant CAEPs when stimuli were present and reporting the absence of CAEPs when no stimuli were present. Research Design: A repeated-measures design was used where infant-generated CAEPs were interpreted by examiners and an automated statistic. Study Sample: There were nine male and five female infants (mean age, 12 mo; SD, 3.4) who completed behavioral and electrophysiological testing using speech-based stimuli. Data Collection and Analysis: In total, 87 infant CAEPs were recorded to three sensation levels, 10, 20 and 30 dB relative to the behavioral thresholds and to nonstimulus trials. Three examiners were presented with these responses: (1) “in series,” where waveforms were presented in order of decreasing stimulus presentation levels, and (2) “nonseries,” where waveforms were randomized completely and presented as independent waveforms. The examiners were given no information about the stimulus levels and were asked to determine whether responses to auditory stimulation could be observed and their degree of certainty in making their decision. Data from the CAEP responses were also converted to multiple dependent variables and analyzed using Hotelling's T2. Results from both methods of response detection were analyzed using a repeated measures ANOVA (analysis of variance) and parameters of signal detection theory known as d-prime (d′) and the area under the receiver operating characteristic (ROC) curve. Results: Results showed that as the stimulus level increased, the sensitivity index, d′, increased for both methods of response detection, but neither reached the maximum possible d′ value with a sensation level of 30 dB. The examiners with the greatest experience and Hotelling's T2 were equally sensitive in differentiating the CAEP from noise. Conclusions: Hotelling's T2 appears to detect CAEPs from normal hearing infants at a rate equal to that of an experienced examiner. A clinical instrument that applies Hotelling's T2 on-line, so that the likelihood of response detection can be assessed objectively, should be of particular benefit to the novice or less experienced examiner.


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