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Information Journal Paper

Title

COMPARISON OF CONFIDENCE INTERVAL BASED ON BOOTSTRAP METHOD FOR THE MEAN RESPONSE TIME IN A SIMULATION STUDY

Author(s)

 KAZEMZADEH GAREHCHOBOGH HOSSEIN | TARVIRDIZADE BAHMAN | AFSHARI SAFAVI ALIREZA | Issue Writer Certificate 

Pages

  107-130

Abstract

 The MEAN RESPONSE TIME plays an important role in the analyzing and optimizing the queuing system, which determines the number and type of giving service. In this paper, new confidence intervals of MEAN RESPONSE TIME for an M/G/1 FCFS queuing system is contrasted based on the NONPARAMETRIC DELTA METHOD and five bootstrap methods. These methods include: NONPARAMETRIC DELTA METHOD confidence interval based on the INFLUENCE FUNCTION, standard bootstrap confidence interval, percentile bootstrap confidence interval, bootstrap-t confidence interval, bias corrected, acceleration bootstrap confidence interval, and BOOTSTRAP PIVOTAL CONFIDENCE INTERVAL. In a simulation study, these six methods are compared and evaluated the accuracy and performance of the confidence intervals for three different M/G/1 FCFS queuing systems based on the coverage percentage and the average length of confidence intervals.

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    APA: Copy

    KAZEMZADEH GAREHCHOBOGH, HOSSEIN, TARVIRDIZADE, BAHMAN, & AFSHARI SAFAVI, ALIREZA. (2014). COMPARISON OF CONFIDENCE INTERVAL BASED ON BOOTSTRAP METHOD FOR THE MEAN RESPONSE TIME IN A SIMULATION STUDY. ADVANCES IN MATHEMATICAL MODELING, 4(1), 107-130. SID. https://sid.ir/paper/243868/en

    Vancouver: Copy

    KAZEMZADEH GAREHCHOBOGH HOSSEIN, TARVIRDIZADE BAHMAN, AFSHARI SAFAVI ALIREZA. COMPARISON OF CONFIDENCE INTERVAL BASED ON BOOTSTRAP METHOD FOR THE MEAN RESPONSE TIME IN A SIMULATION STUDY. ADVANCES IN MATHEMATICAL MODELING[Internet]. 2014;4(1):107-130. Available from: https://sid.ir/paper/243868/en

    IEEE: Copy

    HOSSEIN KAZEMZADEH GAREHCHOBOGH, BAHMAN TARVIRDIZADE, and ALIREZA AFSHARI SAFAVI, “COMPARISON OF CONFIDENCE INTERVAL BASED ON BOOTSTRAP METHOD FOR THE MEAN RESPONSE TIME IN A SIMULATION STUDY,” ADVANCES IN MATHEMATICAL MODELING, vol. 4, no. 1, pp. 107–130, 2014, [Online]. Available: https://sid.ir/paper/243868/en

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