Abstract
| Original language | Undefined |
|---|---|
| Article number | 10.1080/02331880500310181 |
| Pages (from-to) | 429-443 |
| Number of pages | 15 |
| Journal | Statistics |
| Volume | 39 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 2005 |
Keywords
- EWI-12819
- MSC-62G15
- MSC-62P30
- Exceedance probability
- Statistical Process Control
- Phase II control limits
- IR-64795
- Empirical quantiles
Cite this
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Exceedance probabilities for parametric control charts. / Albers, Willem/Wim; Kallenberg, W.C.M.; Sri Nurdiati, S.N.
In: Statistics, Vol. 39, No. 5, 10.1080/02331880500310181, 2005, p. 429-443.Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - Exceedance probabilities for parametric control charts
AU - Albers, Willem/Wim
AU - Kallenberg, W.C.M.
AU - Sri Nurdiati, S.N.
PY - 2005
Y1 - 2005
N2 - Common control charts assume normality and known parameters. Quite often these assumptions are not valid and large relative errors result in the usual performance characteristics, such as the false alarm rate or the average run length. A fully nonparametric approach can form an attractive alternative but requires more Phase I observations than are usually available. Sufficiently large parametric families then provide realistic intermediate models. In this paper the performance of charts based on such families is considered. Exceedance probabilities of the resulting stochastic performance characteristics during in-control are studied. Corrections are derived to ensure that such probabilities stay within prescribed bounds. Attention is also devoted to the impact of the corrections for an out-of-control process. Simulations are presented both for illustration and to demonstrate that the approximations obtained are sufficiently accurate for use in practice.
AB - Common control charts assume normality and known parameters. Quite often these assumptions are not valid and large relative errors result in the usual performance characteristics, such as the false alarm rate or the average run length. A fully nonparametric approach can form an attractive alternative but requires more Phase I observations than are usually available. Sufficiently large parametric families then provide realistic intermediate models. In this paper the performance of charts based on such families is considered. Exceedance probabilities of the resulting stochastic performance characteristics during in-control are studied. Corrections are derived to ensure that such probabilities stay within prescribed bounds. Attention is also devoted to the impact of the corrections for an out-of-control process. Simulations are presented both for illustration and to demonstrate that the approximations obtained are sufficiently accurate for use in practice.
KW - EWI-12819
KW - MSC-62G15
KW - MSC-62P30
KW - Exceedance probability
KW - Statistical Process Control
KW - Phase II control limits
KW - IR-64795
KW - Empirical quantiles
U2 - 10.1080/02331880500310181
DO - 10.1080/02331880500310181
M3 - Article
VL - 39
SP - 429
EP - 443
JO - Statistics
JF - Statistics
SN - 0233-1888
IS - 5
M1 - 10.1080/02331880500310181
ER -