fitdistrplus

fitdistrplus is an R package designed for fitting and visualizing probability distributions to data. It provides a unified interface for working with various types of distributions, including discrete and continuous ones. The primary function of the package is to estimate the parameters of a chosen distribution that best represent the observed data. This is achieved through different estimation methods, such as maximum likelihood estimation (MLE) and minimum chi-squared estimation.

The package offers several graphical tools to assess the goodness-of-fit of the estimated distribution. These include density plots overlaid with the fitted distribution, cumulative distribution function (CDF) plots, and QQ-plots. These visualizations help users visually evaluate how well the chosen distribution captures the characteristics of their data.

fitdistrplus supports a wide range of common distributions, and users can also define and fit custom distributions. The output of the fitting process includes estimated parameters, standard errors, and various fit statistics. This makes it a versatile tool for statisticians, data scientists, and researchers who need to model their data using probability distributions in R.