Bayesian estimation for kumaraswamy shanker distribution with applications of COVID-19 data

Abstract EN

In this paper, a new three-parameter distribution called the Kumaraswamy Shanker (Kw-Sh) distribution is proposed and studied.

the reliability (survival) function, hazard rate function, reversed hazard rate function r and the cumulative hazard rate function of the new distribution is obtained.

some mathematical properties of this distribution such as moments, moments generating function, incomplete moments, quantile function, entropies (Renyi and Shannon) and mean deviation are derived.

the method of maximum likelihood and Bayesian estimation method are used to estimate the distribution parameters.

finally, two real datasets, related to COVID-19, were used to examine the performance of the proposed distribution compared to Shanker and exponential distributions based on Akaike information criterion (AIC).

the results showed that the new distribution is more proper in fitting data than other distributions.

also, the estimation of parameters using the Bayesian method is better than the maximum likelihood method.