Abstract
Earthquakes are one of the main natural hazards which seriously make threats the life and property of human beings. Different probability distributions of the earthquake magnitude levels in Bangladesh are fitted. In terms of graphical assessment and goodness-of-fit criterion, the log-normal distribution is found to be the best fit probability distributions for the earthquake magnitude levels in Bangladesh among the probability distribution considered in this study. The average earthquake magnitude level found 4.67 (in Richter scale) for log-normal distribution and the approximately forty-six percent chance is predicted to take place earthquake magnitude in the interval four to five.
Highlights
Bangladesh is the most earthquake venerable countries of the globe
A lot of probability distribution functions have been proposed in recent past, but in present study Normal, Log-normal, Weibull, Gamma, Cauchy, Logistic, and Gumbel (Gumbel, 1960) are used to describe the characteristics of earthquake magnitude levels in Bangladesh
The probability density function (PDF) of the log-normal distribution is given by Johnson et al (1994)
Summary
Bangladesh is the most earthquake venerable countries of the globe. Bangladesh is a South-Asian developing country which is used to struggle with a mixture of natural disasters and the earthquake is one of them. Understanding the patterns in the frequency of natural events such as earthquakes is very important as it helps in the prediction of their future occurrence and provides better protection for human and different other lives Distributions describing these events are known to be standard distributions unsuitable for modeling the frequency of such events. The fitting distribution to atmospheric data like earthquake magnitude is one of the very frequent tasks that choose probability distribution to model a random variable along with the estimates of the parameter(s) of the chosen distribution under efficient expertise and valid judgment, which generally necessitates iterative process of distribution choice, parameter estimation, and determining quality-of-fit assessment It is finds interest in the field of meteorology (for any atmospheric parameter) to provide a good fit of atmospheric data which strongly depends on the fitting of the probability distribution
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