References
1. Kang, L. and Albin, S.L. \On-line monitoring when
the process yields a linear pro le", Journal of Quality
Technology, 32(4), pp. 418{426 (2000).
2. Noorossana, R., Saghaei, A., and Amiri, A., Statistical
Analysis of Pro le Monitoring, 1st Edn., In Wiley
Series in Probability and Statistics (2011).
3. Niaki, S.T.A. and Khedmati, M. \Identifying the
change time of multivariate binomial processes for step
changes and drifts", Journal of Industrial Engineering
International, 9(1), p. 3 (2013).
4. Kazemzadeh, R.B., Noorossana, R., and Ayoubi, M.
\Change point estimation of multivariate linear pro-
les under linear drift", Communications in Statistics-
Simulation and Computation, 44(6), pp. 1570{1599
(2015).
5. Korkas, K.K. and PryzlewiczV, P. \Multiple changepoint
detection for non-stationary time series using
wild binary segmentation", Statistica Sinica, pp. 287{
311 (2017).
6. Atashgar, K. \Identi cation of the change point: an
overview", The International Journal of Advanced
Manufacturing Technology, 64(9{12), pp. 1663{1683
(2013).
7. Aminikhanghahi, S. and Cook, D.J. \A survey of methods
for time series change point detection", Knowledge
and Information Systems, 51(2), pp. 339{367 (2017).
8. Woodall, W.H., Spitzner, D.J., Montgomery, D.C.,
and Gupta, S. \Using control charts to monitor process
and product quality pro les", Journal of Quality
Technology, 36(3), pp. 309{320 (2004).
9. Qiu, P. \Distribution-free multivariate process control
based on log-linear modeling", IIE Transactions,
40(7), pp. 664{677 (2008).
570 S. Hajifar and H. Mahlooji/Scientia Iranica, Transactions E: Industrial Engineering 28 (2021) 557{571
10. Yeh, A.B., Huwang, L., and Li, Y.M. \Pro le monitoring
for a binary response", IIE Transactions, 41(11),
pp. 931{941 (2009).
11. Paynabar, K., Jin, J., and Yeh, A.B. \Phase I riskadjusted
control charts for monitoring surgical performance
by considering categorical covariates", Journal
of Quality Technology, 44(1), pp. 39{53 (2012).
12. Soleymanian, M.E., Khedmati, M., and Mahlooji, H.
\Phase II monitoring of binary response pro les", Scientia
Iranica, Transaction E, Industrial Engineering,
20(6), p. 2238 (2013).
13. Koosha, M. and Amiri, A. \Generalized linear mixed
model for monitoring autocorrelated logistic regression
pro les", The International Journal of Advanced Manufacturing
Technology, 64(1{4), pp. 487{495 (2013).
14. Amiri, A., Koosha, M., and Azhdari, A. \T2 based
methods for monitoring gamma pro les", In International
Conference on Industrial Engineering and
Operations Management, pp. 580{585 (2012).
15. Noorossana, R., Aminnayeri, M., and Izadbakhsh, H.
\Statistical monitoring of polytomous logistic pro les
in phase II", Scientia Iranica, 20(3), pp. 958{966
(2013).
16. Amiri, A., Koosha, M., Azhdari, A., and Wang, G.
\Phase I monitoring of generalized linear model-based
regression pro les", Journal of Statistical Computation
and Simulation, 85(14), pp. 2839{2859 (2015).
17. Qi, D., Wang, Z., Zi, X., and Li, Z. \Phase II
monitoring of generalized linear pro les using weighted
likelihood ratio charts", Computers & Industrial Engineering,
94, pp. 178{187 (2016).
18. Sogandi, F. and Amiri, A. \Monotonic change point
estimation of generalized linear model-based regression
pro les", Communications in Statistics-Simulation
and Computation, 46(3), pp. 2207{2227 (2017).
19. Khedmati, M. and Niaki, S.T.A. \Phase II monitoring
of general linear pro les in the presence of betweenpro
le autocorrelation", Quality and Reliability Engineering
International, 32(2), pp. 443{452 (2016).
20. Noorossana, R., Saghaei, A., Paynabar, K., and Abdi,
S. \Identifying the period of a step change in highyield
processes", Quality and Reliability Engineering
International, 25(7), pp. 875{883 (2009).
21. Perry, M.B., Pignatiello Jr, J.J., and Simpson, J.R.
\Estimating the change point of a Poisson rate parameter
with a linear trend disturbance", Quality and
Reliability Engineering International, 22(4), pp. 371{
384 (2006).
22. Noorossana, R. and Shadman, A. \Estimating the
change point of a normal process mean with a monotonic
change", Quality and Reliability Engineering
International, 25(1), pp. 79{90 (2009).
23. Alaeddini, A., Ghazanfari, M., and Nayeri, M.A. \A
hybrid fuzzy-statistical clustering approach for estimating
the time of changes in xed and variable sampling
control charts", Information Sciences, 179(11),
pp. 1769{1784 (2009).
24. Atashgar, K. and Noorossana, R. \An integrating approach
to root cause analysis of a bivariate mean vector
with a linear trend disturbance", The International
Journal of Advanced Manufacturing Technology, 52(1{
4), pp. 407{420 (2011).
25. Ahmadzadeh, F. \Change point detection with multivariate
control charts by arti cial neural network",
The International Journal of Advanced Manufacturing
Technology, 97(9{12), pp. 3179{3190 (2018).
26. Zou, C., Zhou, C., Wang, Z., and Tsung, F. \A selfstarting
control chart for linear pro les", Journal of
Quality Technology, 39(4), pp. 364{375 (2007).
27. Paynabar, K., Zou, C., and Qiu, P. \A change-point
approach for phase-I analysis in multivariate pro le
monitoring and diagnosis", Technometrics, 58(2), pp.
191{204 (2016).
28. Maleki, M.R., Amiri, A., and Taheriyoun, A.R. \Identifying
the time of step change and drift in phase
II monitoring of autocorrelated logistic regression
pro les", Scientia Iranica, Transactions E, Industrial
Engineering, 25(6), pp. 3654{3666 (2018).
29. Firth, D. \Bias reduction of maximum likelihood
estimates", Biometrika, 80(1), pp. 27{38 (1993).
30. Shadman, A., Zou, C., Mahlooji, H., and Yeh, A.B.
\A change point method for Phase II monitoring
of generalized linear pro les", Communications in
Statistics-Simulation and Computation, 46(1), pp.
559{578 (2017).
31. Margavio, T.M., Conerly, M.D., Woodall, W.H., and
Drake, L.G. \Alarm rates for quality control charts",
Statistics & Probability Letters, 24(3), pp. 219{224
(1995).
32. Hawkins, D.M., Qiu, P., and Kang, C.W. \The change
point model for statistical process control", Journal of
Quality Technology, 35(4), pp. 355{366 (2003).
33. Heinze, G. and Schemper, M. \A solution to the
problem of separation in logistic regression", Statistics
in Medicine, 21(16), pp. 2409{2419 (2002).
34. Kosmidis, I. and Firth, D. \A generic algorithm for
reducing bias in parametric estimation", Electronic
Journal of Statistics, 4, pp. 1097{1112 (2010).
35. Heinze, G. and Schemper, M. \A solution to the
problem of separation in logistic regression", Statistics
in Medicine, 21(16), pp. 2409{2419 (2002).
36. Shadman, A., Mahlooji, H., Yeh, A.B., and Zou, C. \A
change point method for monitoring generalized linear
pro les in phase I", Quality and Reliability Engineering
International, 31(8), pp. 1367{1381 (2015).
S. Hajifar and H. Mahlooji/Scientia Iranica, Transactions E: Industrial Engineering 28 (2021) 557{571 571
37. Ver Hoef, J.M. and Boveng, P.L. \Quasi-Poisson vs.
negative binomial regression: how should we model
overdispersed count data?", Ecology, 88(11), pp. 2766{
2772 (2007).
)
