Finding the best distribution that fits a data sample seems to be a though problem since there is no cookie-cutter solution.
Although automated fit softwares exist, it remains suboptimal to use a list of well-known distribution.
I heard about the function fitdistr() in the MASS package but some people argue that there is no best way to fit data properly with this kind of method as well as using likelihood methods for all data sample.
My questions are: - Do those packages or automated fit softwares work for business analysis where strict accuracy doesn't matter ? - What is the investigation method to find the distribution of a data sample without using a predefined list of distribution ? Is it based on guess ? Experience ? Methodology ? If it is based on methodology, what is it ?
I'm not a scientist so I may have difficulties to understand the concepts. I'm in business and don't need to be 100% accurate in my analysis. I just want to find a way to find the distribution of my data without force-fitting them with a normal distribution or that kind of wrong analysis. I'm using R.