Open AccessUsing Cauchy Distribution To Estimate Survival Function
Author(s) -
Hind Jawad Kadhim Al Bderi
Publication year - 2021
Publication title -
türk bilgisayar ve matematik eğitimi dergisi
Language(s) - English
Resource type - Journals
ISSN - 1309-4653
DOI - 10.17762/turcomat.v12i4.591
Subject(s) - mathematics , cauchy distribution , estimator , measure (data warehouse) , statistics , mean squared error , function (biology) , least squares function approximation , cumulative distribution function , m estimator , probability density function , mathematical optimization , computer science , database , evolutionary biology , biology
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”