Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
The effect of Phase I sample size on the run length performance of control charts for autocorrelated data
Date
2008-01-01
Author
Köksal, Gülser
Ula, Taylan Ali
Testik, Murat Caner
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
201
views
0
downloads
Cite This
Traditional control charts assume independence of observations obtained from the monitored process. However, if the observations are autocorrelated, these charts often do not perform as intended by the design requirements. Recently, several control charts have been proposed to deal with autocorrelated observations. The residual chart, modified Shewhart chart, EWMAST chart, and ARMA chart are such charts widely used for monitoring the occurrence of assignable causes in a process when the process exhibits inherent autocorrelation. Besides autocorrelation, one other issue is the unknown values of true process parameters to be used in the control chart design, which are often estimated from a reference sample of in-control observations. Performances of the above-mentioned control charts for autocorrelated processes are significantly affected by the sample size used in a Phase I study to estimate the control chart parameters. In this study, we investigate the effect of Phase I sample size on the run length performance of these four charts for monitoring the changes in the mean of an autocorrelated process, namely an AR(1) process. A discussion of the practical implications of the results and suggestions on the sample size requirements for effective process monitoring are provided.
Subject Keywords
Statistics, Probability and Uncertainty
,
Statistics and Probability
URI
https://hdl.handle.net/11511/45143
Journal
JOURNAL OF APPLIED STATISTICS
DOI
https://doi.org/10.1080/02664760701683619
Collections
Department of Industrial Engineering, Article
Suggestions
OpenMETU
Core
A marginalized multilevel model for bivariate longitudinal binary data
Inan, Gul; İlk Dağ, Özlem (Springer Science and Business Media LLC, 2019-06-01)
This study considers analysis of bivariate longitudinal binary data. We propose a model based on marginalized multilevel model framework. The proposed model consists of two levels such that the first level associates the marginal mean of responses with covariates through a logistic regression model and the second level includes subject/time specific random intercepts within a probit regression model. The covariance matrix of multiple correlated time-specific random intercepts for each subject is assumed to ...
Robust estimation and hypothesis testing under short-tailedness and inliers
Akkaya, Ayşen (Springer Science and Business Media LLC, 2005-06-01)
Estimation and hypothesis testing based on normal samples censored in the middle are developed and shown to be remarkably efficient and robust to symmetric short-tailed distributions and to inliers in a sample. This negates the perception that sample mean and variance are the best robust estimators in such situations (Tiku, 1980; Dunnett, 1982).
Analysis of Covariance with Non-normal Errors
ŞENOĞLU, BİRDAL; Avcioglu, Mubeccel Didem (Wiley, 2009-12-01)
P>Analysis of covariance techniques have been developed primarily for normally distributed errors. We give solutions when the errors have non-normal distributions. We show that our solutions are efficient and robust. We provide a real-life example.
Models of response error components in supervised interview-reinterview surveys
Ayhan, Hüseyin Öztaş (Informa UK Limited, 2003-11-01)
The current work deals with modelling of response error components in supervised interview-reinterview surveys. The model considers several stages of an interactive process to obtain and record a response. The response process is evaluated as, controller-interviewer-respondent-interviewer-controller interaction setting under a supervised interviewing process. The allocation of controllers, interviewers and respondents is made by a hierarchical design for the interview-reinterview process. In addition, a cod...
Autoregressive models with short-tailed symmetric distributions
Akkaya, Ayşen (Informa UK Limited, 2008-01-01)
Symmetric short-tailed distributions do indeed occur in practice but have not received much attention particularly in the context of autoregression. We consider a family of such distributions and derive the modified maximum likelihood estimators of the parameters. We show that the estimators are efficient and robust. We develop hypothesis-testing procedures.
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
G. Köksal, T. A. Ula, and M. C. Testik, “The effect of Phase I sample size on the run length performance of control charts for autocorrelated data,”
JOURNAL OF APPLIED STATISTICS
, pp. 67–87, 2008, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/45143.