The Weibull-Inverse Lomax (WIL) distribution with Application on Bladder Cancer

Abstract

In this paper, we introduced a four-parameter probability model called Weibull-Inverse Lomax distribution with decreasing, increasing and bathtub hazard rate function. The WIL distribution density function is J-shaped, positively skewed, and J-shaped in reverse. Some of the mentioned distribution's statistical characteristics are provided including moments, order statistics, entropy, mean, variance, moment generating function, and quantile function. The method of maximum likelihood estimation was used to estimate the parameters of the model. The distribution's importance is proved by its implementation to the bladder cancer data set. Goodness-of-fit of this distribution by various techniques demonstrates that the WIL distribution is empirically better for lifetime application.

A New Inverse Lomax Weibull-G Family of Distributions with Application To Carbon Fibre Data

“…For instance, if you have data that shows the time it takes for a specific event to occur and it is right-skewed, you should consider using both the Inverse Lomax and Weibull distributions to analyze it thoroughly. By examining the parameters of both distributions, you can obtain a more comprehensive understanding of the underlying events and make better predictions or conclusions about the data ( [11], [12], and [13]). Some of the families of Inverse Lomax distribution include the Inverse Lomax G by [1], the Inverse Lomax exponentiated G by [14], the Sine Inverse Lomax G by [15], as well as Truncated Inverse Lomax G by [16].…”

On New Weibull Inverse Lomax Distribution with Applications

“…al. 13 extended the ILD with the Weibull G family by Bourgnuignon 14 in 2014. They called it Weibull Inverse Lomax (WIL).…”

The Zubair-Inverse Lomax Distribution with Applications

“…Other family members include Singh maddala, Pareto, log-Logistics, Dagum, generalized second-type beta distributions among others as in [1]. Since then, IL distribution has gained a lot of coverage in many fields such as Actuarial Science and Economics (see [1]), Geophysical data (see [2]), Survival analysis (see [3]), and Medical Science (see [4] and [5]). Recently, [6] considered multicomponent stress-strength reliability for the IL distribution with different shape parameters.…”