Confidence Interval Estimation of the Conditional Reliability Function for Time Domain Data

Authors

  • Lutfiah Ismail Al turk Statistics Department, Faculty of Sciences, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia

Keywords:

NHPP log-logistic model, maximum likelihood estimation, confidence interval, conditional reliability function, observed interval length.

Abstract

The function of conditional reliability gives the probability of successfully implementing another operation following the successful implementation of a previous operation. The prediction of this function can help software developers in determining optimal release times. In this paper, the Maximum Likelihood Estimation (MLE) method is used to estimate the Non-Homogeneous Poisson Process Log-Logistic (NHPP LL) model’s parameters. The upper and the lower bounds of the parameters and conditional reliability function of time domain data are obtained. Real data application is conducted using the coefficient of multiple determination criteria and observed interval length to evaluate the performance of the NHPP LL model and the constructed confidence intervals, respectively. Our results encourage for more assessment of confidence intervals of other measures of reliability of the NHPP models.

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Published

2019-02-16

How to Cite

Ismail Al turk, L. (2019). Confidence Interval Estimation of the Conditional Reliability Function for Time Domain Data. American Scientific Research Journal for Engineering, Technology, and Sciences, 52(1), 197–208. Retrieved from https://asrjetsjournal.org/index.php/American_Scientific_Journal/article/view/4671

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