The optimal choice of negative binomial charts for monitoring high-quality processes

Willem Albers*

*Corresponding author for this work

    Research output: Contribution to journalArticleAcademicpeer-review

    31 Citations (Scopus)
    2 Downloads (Pure)


    Good control charts for high quality processes are often based on the number of successes between failures. Geometric charts are simplest in this respect, but slow in recognizing moderately increased failure rates p. Improvement can be achieved by waiting until r > 1 failures have occurred, i.e. by using negative binomial charts.In this paper we analyze such charts in some detail. On the basis of a fair comparison, we demonstrate how the optimal r is related to the degree of increase of p. As in practice p will usually be unknown, we also analyze the estimated version of the charts. In particular, simple corrections are derived to control the non-negligible effects of this estimation step.
    Original languageEnglish
    Pages (from-to)214-225
    Number of pages12
    JournalJournal of statistical planning and inference
    Issue number1
    Publication statusPublished - 2010


    • MSC-62C05
    • MSC-62F12
    • MSC-62P10
    • Geometric charts
    • Health care monitoring
    • Average run length
    • Statistical process control
    • Estimated parameters


    Dive into the research topics of 'The optimal choice of negative binomial charts for monitoring high-quality processes'. Together they form a unique fingerprint.

    Cite this