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Advances in Degradation Modeling pp 397–414Cite as

Probability Plotting with Independent Competing Risks

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Abstract

In this chapter, we discuss probability plotting for competing risk data in the presence of Type I or right censoring. The construction of probability plots is based on the linearization of the cumulative distribution function of the first-order statistic. We consider the case when risks are independent. We describe procedures for constructing pointwise confidence intervals based on large-sample properties of maximum likelihood estimators. The proposed method is compared with traditional probability plotting that assumes that causes of failure can be eliminated.

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Author information

Authors and Affiliations

  1. Department of Statistics, Washington State University, Pullman, WA, USA

    Francis G. Pascual

  2. Axio Research Acquisition Co. LLC, Seattle, WA, USA

    Christopher Gast

Authors
  1. Francis G. Pascual
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  2. Christopher Gast
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Editor information

Editors and Affiliations

  1. Université Victor Segalen Bordeaux 2, I’lnstitut de Mathématiques de Bordeaux, Bordeaux Cedex, 33076, France

    M.S. Nikulin

  2. Département Génie Informatique, Labo. Mathématiques Appliquées Compiègne, Université de Technologie de Compiègne, Compiègne, France

    Nikolaos Limnios

  3. McMaster University, Department of Mathematics and Statistics, 1280 Main Street West, Hamilton, L8S 4K1, Canada

    N. Balakrishnan

  4. Fak. Mathematik, Inst. Mathematische Stochastik, Otto-von-Guericke-Universität, Universitätsplatz 2, Magdeburg, 39106, Germany

    Waltraud Kahle

  5. Laboratoire de Statistique Medicale, Université René Descartes, Paris 5, Paris, 75006, France

    Catherine Huber-Carol

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© 2010 Birkhaüser Boston, a part of Springer Science+Business Media, LLC

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Pascual, F.G., Gast, C. (2010). Probability Plotting with Independent Competing Risks. In: Nikulin, M., Limnios, N., Balakrishnan, N., Kahle, W., Huber-Carol, C. (eds) Advances in Degradation Modeling. Statistics for Industry and Technology. Birkhäuser Boston. https://doi.org/10.1007/978-0-8176-4924-1_26

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