MAXIMUM LIKELIHOOD BASED ON NEWTON RAPHSON, FISHER SCORING AND EXPECTATION MAXIMIZATION ALGORITHM APPLICATION ON ACCIDENT DATA.

The parameter estimate is the value of the parameter based on data or samples taken from a certain popolation. There are several methods to estimate the parameters of one of them is Maximum Likelihood Estimation (MLE). MLE is a distribution approach by maximizing likelihood function. The purpose of this study is to estimate the parameter value of a data distributed with Maximum Likelihood based on the iteration algorithm. The iteration algorithm that will be used is Newton Raphson, Fisher Scoring and Expectation Maximization Algorithm with the help of Matlab 2016a. The purpose of this paper is to look at the parameter values of three algorithms that have the same results or have great results and with regard to the number of iterations performed by the three algorithms. In this paper the three algorithms will be applied to the accident data.