Bayesian estimation of the survival function of the Consul Kumaraswamy distribution

Abstract

One of the problems facing the data analyst is to find the appropriate statistical model that describes the studied phenomenon, because there are many estimation methods used in finding the estimates of the survival function, which represents the probability of the organism surviving after the passage of time t. By Standard Informative Bayesian Estimator and Expected Bayesian Estimator with symmetric squared error loss function and asymmetric General Entropy Loss function, and by Monte Carlo simulation, it was obtained Estimated survival function values ​​for Consul kumaraswamy distribution (CKSD) for a sample size of (50) individuals, which represents the number of patients with ischemic heart disease