Estimation of \(R=P[Y < X]\) for Burr type XII distribution based on ranked set sampling

  • Authors

    • Amal Hassan Institute of Statistical Studies and Research, Cairo University
    • Salwa Assar Institute of Statistical Studies and Research, Cairo University
    • Marwa Yahia Institute of Statistical Studies and Research, Cairo University
    2014-07-19
    https://doi.org/10.14419/ijbas.v3i3.2820

  • Abstract

    Ranked set sampling (RSS) is a statistical technique for data collection that generally leads to more efficient estimators than competitors based on simple random sample (SRS). In the current paper, the estimation of R=P[Y<X] when Y and X are two independent Burr type XII distribution with common known shape parameter c will be considered. Maximum likelihood estimator is proposed to estimate R based on ranked set sampling data. These estimators will be compared in terms of their biases, mean square errors and efficiencies with known estimators based on SRS data. It is shown that the estimators based on RSS are more efficient than the corresponding SRS. The results are illustrated using simulated data.

    Keywords: Burr Type XII, Stress Strength Model, Ranked Set Sampling, Method of Maximum Likelihood.

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  • How to Cite

    Hassan, A., Assar, S., & Yahia, M. (2014). Estimation of \(R=P[Y < X]\) for Burr type XII distribution based on ranked set sampling. International Journal of Basic and Applied Sciences, 3(3), 274-280. https://doi.org/10.14419/ijbas.v3i3.2820

    Received date: 2014-05-16

    Accepted date: 2014-06-14

    Published date: 2014-07-19