Using Cauchy Distribution To Estimate Survival Function

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Hind Jawad Kadhim Al Bderi

Abstract

This paper intends to estimate the unlabeled two parameters for Cauchy distribution model depend on employing the maximum likelihood estimator method  to obtain the derivation of the point estimators for all unlabeled parameters depending on iterative techniques , as Newton – Raphson method , then to derive “Lindley approximation estimator method and then to derive Ordinary least squares estimator method. Applying all these methods to estimate related probability functions; death density function, cumulative distribution function, survival function and hazard function (rate function)”.


“When examining the numerical results for probability survival function by employing mean squares error measure and mean absolute percentage measure, this may lead to work on the best method in modeling a set of real data”

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How to Cite
Kadhim Al Bderi, H. J. . (2021). Using Cauchy Distribution To Estimate Survival Function. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(4), 1014–1023. Retrieved from https://turcomat.org/index.php/turkbilmat/article/view/591 (Original work published April 11, 2021)
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