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Description: |
Counts of nonconformities are frequently assumed to have a Poisson distribution. The integer and asymmetrical character of this distribution and the value of its target mean may prevent the quality control operator to deal with a chart with a pre-specified in-control average run length (ARL) and the ability to promptly detect both increases and decreases in the mean of those counts. Moreover, as far as we know, the c-chart proposed to monitor the mean of first-order integer-valued autoregressive (INAR(1)) Poisson counts tends to be ARL-biased, in the sense that it takes longer, in average, to detect some shifts in the process mean than to trigger a false alarm.
In this talk, we capitalize on the randomization of the emission of a signal and on a nested secant rule search procedure not only to eliminate the bias of the ARL function of the c-chart for the mean of INAR(1) Poisson counts, but also to bring its in-control ARL exactly to a pre-specified and desired value. Striking illustrations of the resulting ARL-unbiased c-charts are provided.
Joint work with Sofia Paulino and Sven Knoth.
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Date: |
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| Start Time: |
14:30 |
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Speaker: |
Manuel Cabral Morais (CEMAT, Univ. Lisboa)
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Institution: |
CEMAT, Univ. Lisboa
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Place: |
Sala 5.5
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| Research Groups: |
-Probability and Statistics
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See more:
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<Main>
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