A Comprehensive Guide to Maximum Likelihood Estimation and Bayesian Estimation

An estimation function is a function that helps in estimating the parameters of any statistical model based on data that has random values. The estimation is a process of extracting parameters from the observation that are randomly distributed. In this article, we are going to have an overview of the two estimation functions - Maximum Likelihood Estimation and Bayesian Estimation. Before having an understanding of these two, we will try to understand the probability distribution on which both of these estimation functions are dependent. The major points to be discussed in this article are listed below. Table of Contents Probability DistributionMaximum Likelihood Estimation (MLE)Bayesian EstimationMaximum Likelihood Estimation (MLE) vs Bayesian Estimation Now let us start with understanding the probability distribution. Probability Distribution In statistics, the probability distribution is a function that represents the probability of occurrence of different outcomes fro