### Abstract

When the distributional form of the observations differs from normality, standard control charts are often seriously in error. Such model errors can be avoided with (modified) nonparametric control charts. Unfortunately, these control charts suffer from large stochastic errors due to estimation. In between are so called parametric control charts. All three of them are discussed in this paper as well as a combined chart, which chooses one of the three control charts according to the appropriate model assumption on the underlying distribution. The data themselves tell us which of the three control charts to select. Ready-made formulas for the several control charts are presented accompanied by an application on real data. Apart from bias removal, criteria based on exceedance probability and semi-variance are investigated.

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

Place of Publication | Enschede |

Publisher | University of Twente, Department of Applied Mathematics |

Number of pages | 15 |

Publication status | Published - 2004 |

### Publication series

Name | Memorandum |
---|---|

Publisher | University of Twente, Department of Applied Mathematics |

No. | 1713 |

### Keywords

- EWI-3533
- MSC-62G32
- IR-60819
- MSC-65C05
- METIS-218216
- MSC-62P30

## Cite this

Albers, WW., & Kallenberg, W. C. M. (2004).

*Self adapting control charts*. (Memorandum; No. 1713). Enschede: University of Twente, Department of Applied Mathematics.