### Abstract

Original language | Undefined |
---|---|

Place of Publication | Enschede |

Publisher | University of Twente, Department of Applied Mathematics |

Number of pages | 32 |

Publication status | Published - 2002 |

### Publication series

Name | Memorandum Faculty of Mathematical Sciences |
---|---|

Publisher | University of Twente, Faculty of Mathematical Sciences |

No. | 1623 |

ISSN (Print) | 0169-2690 |

### Keywords

- MSC-62P30
- MSC-65C05
- METIS-206702
- IR-65810
- EWI-3443
- MSC-62F12

### Cite this

*Parametric control charts*. (Memorandum Faculty of Mathematical Sciences; No. 1623). Enschede: University of Twente, Department of Applied Mathematics.

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*Parametric control charts*. Memorandum Faculty of Mathematical Sciences, no. 1623, University of Twente, Department of Applied Mathematics, Enschede.

**Parametric control charts.** / Albers, Willem/Wim; Kallenberg, W.C.M.; Nurdiati, S.

Research output: Book/Report › Report › Professional

TY - BOOK

T1 - Parametric control charts

AU - Albers, Willem/Wim

AU - Kallenberg, W.C.M.

AU - Nurdiati, S.

N1 - Imported from MEMORANDA

PY - 2002

Y1 - 2002

N2 - Standard control charts are based on the assumption that the observations are normally distributed. In practice, normality often fails and consequently the false alarm rate is seriously in error. Application of a nonparametric approach is only possible with many Phase I observations. Since nowadays such very large sample sizes are usually not available, there is need for an intermediate approach by considering a larger parametric model containing the normal family as a submodel. In this paper control limits are presented in such larger parametric models, with emphasis on the so called normal power family. Correction terms are derived, taking into account that the parameters are estimated. Simulation results show that the control limits are accurate, not only in the considered parametric family, but also for common distributions outside the parametric family, thus covering a broad class of distributions.

AB - Standard control charts are based on the assumption that the observations are normally distributed. In practice, normality often fails and consequently the false alarm rate is seriously in error. Application of a nonparametric approach is only possible with many Phase I observations. Since nowadays such very large sample sizes are usually not available, there is need for an intermediate approach by considering a larger parametric model containing the normal family as a submodel. In this paper control limits are presented in such larger parametric models, with emphasis on the so called normal power family. Correction terms are derived, taking into account that the parameters are estimated. Simulation results show that the control limits are accurate, not only in the considered parametric family, but also for common distributions outside the parametric family, thus covering a broad class of distributions.

KW - MSC-62P30

KW - MSC-65C05

KW - METIS-206702

KW - IR-65810

KW - EWI-3443

KW - MSC-62F12

M3 - Report

T3 - Memorandum Faculty of Mathematical Sciences

BT - Parametric control charts

PB - University of Twente, Department of Applied Mathematics

CY - Enschede

ER -