Application of Expectation Maximization Algorithm in Estimating Parameter Values of Maximum Likelihood Model - Simarmata, Justin Eduardo; H. Bete; S. A. Purba (Talenta Publisher, 2021)
Parameter estimation is an estimation of the population parameter values ​​based on data or samples of population. Parameter estimation can be solverd by several methods, one of which is the Maximum Likelihood method. The focus of this research is to estimate the parameter value of a normal distribution data with Maximum Likelihood based on iteration algorithm. The iteration algorithm that will be used is the Expectation Maximation Algorithm with help of Matlab 2016a program. Based on the results obtained that the estimation value of the parameter and for an accident data in Indonesia based on age group with using Expectation Maximization algorithm is and with 2 iterations.