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One Cut-Point Phase-Type Distributions in Reliability. An Application to Resistive Random Access Memories

Author

Listed:
  • Christian Acal

    (Department of Statistics and O.R. and IMAG, University of Granada, 18071 Granada, Spain)

  • Juan E. Ruiz-Castro

    (Department of Statistics and O.R. and IMAG, University of Granada, 18071 Granada, Spain)

  • David Maldonado

    (Department of Electronics and Computing Technology, University of Granada, 18071 Granada, Spain)

  • Juan B. Roldán

    (Department of Electronics and Computing Technology, University of Granada, 18071 Granada, Spain)

Abstract

A new probability distribution to study lifetime data in reliability is introduced in this paper. This one is a first approach to a non-homogeneous phase-type distribution. It is built by considering one cut-point in the non-negative semi-line of a phase-type distribution. The density function is defined and the main measures associated, such as the reliability function, hazard rate, cumulative hazard rate and the characteristic function, are also worked out. This new class of distributions enables us to decrease the number of parameters in the estimate when inference is considered. Additionally, the likelihood distribution is built to estimate the model parameters by maximum likelihood. Several applications considering Resistive Random Access Memories compare the adjustment when phase type distributions and one cut-point phase-type distributions are considered. The developed methodology has been computationally implemented in R-cran.

Suggested Citation

  • Christian Acal & Juan E. Ruiz-Castro & David Maldonado & Juan B. Roldán, 2021. "One Cut-Point Phase-Type Distributions in Reliability. An Application to Resistive Random Access Memories," Mathematics, MDPI, vol. 9(21), pages 1-13, October.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:21:p:2734-:d:666717
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    References listed on IDEAS

    as
    1. Adele H. Marshall & Mariangela Zenga, 2012. "Experimenting with the Coxian Phase-Type Distribution to Uncover Suitable Fits," Methodology and Computing in Applied Probability, Springer, vol. 14(1), pages 71-86, March.
    2. Elmahdy, Emad E., 2015. "A new approach for Weibull modeling for reliability life data analysis," Applied Mathematics and Computation, Elsevier, vol. 250(C), pages 708-720.
    3. Shakhatreh, Mohammed K. & Lemonte, Artur J. & Moreno–Arenas, Germán, 2019. "The log-normal modified Weibull distribution and its reliability implications," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 6-22.
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