Rayleigh based SPRT: Order Statistics
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Abstract
Noise is integral in the software failure data. A conversion of data is needed to smooth out the noise. Smoothing enhances quality at first as the size increments and turns out to be more regrettable as the gathering size is vast. Order statistics deals with applications of ordered random variables and functions of these variables. When failures are frequent or inter failure time is less, the use of order statistics is significant. Classical Hypothesis testing needs more time to draw conclusions by collecting volumes of data. But, to decide upon the reliability or unreliability of the developed software very quickly Sequential Analysis of Statistical science could be adopted. The method embraced for this is, Sequential Probability Ratio Test (SPRT), which is designed for continuous monitoring. The likelihood based SPRT proposed by Wald is very general and it can be used for many different probability distributions. The method used to derive the unknown parameters is Maximum Likelihood Estimation (MLE). In this paper, a control mechanism based on Order statistics and Sequential Probability Ratio Test is applied using mean value function of Rayleigh distribution and analysed the results.
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