Treffer: The Performance of Phase II Simple Linear Profile Approaches when Parameters Are Estimated

Title:
The Performance of Phase II Simple Linear Profile Approaches when Parameters Are Estimated
Source:
Communications in statistics. Simulation and computation. 41(8-10):1816-1833
Publisher Information:
Colchester: Taylor & Francis, 2012.
Publication Year:
2012
Physical Description:
print, 1 p.1/4
Original Material:
INIST-CNRS
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Department of Statistics, Cairo University, Cairo, Egypt
ISSN:
0361-0918
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Mathematics
Accession Number:
edscal.26164025
Database:
PASCAL Archive

Weitere Informationen

Previous studies of statistical performance of Phase II simple linear profile approaches were reported only for the case of known profile parameters assumption. The main objective of this article is to evaluate and compare the performance of these approaches when the profile parameters are estimated from an in-control Phase I profile data set. Simulations establish that the performance of these approaches is strongly affected when the parameters are estimated compared to the known parameters case. The in-control performance of the competing approaches significantly deteriorates if estimated parameters are used with control limits intended for known parameters, especially when only a few Phase 1 samples are used to estimate the parameters. The results show also that some profile monitoring approaches need much larger number of Phase I profiles than other approaches to achieve the expected statistical performance. They also show that the profile monitoring approach proposed by Mahmoud et al. (2010) has generally better out-of-control run length performance than the competing approaches when the estimated parameters are used in the charts design.