Imputation of missing data and Inference by EM algorithm

Abstract

Missing data is a major issue in many applied problems. in our work we examine data that are missing and . the aims of multiple imputation in comparison to single imputation, we also studying the statistical inference by likelihood Maximum method for sample with missing data with Maximization-Expectation algorithm. Finally, we present the mains packages for imputation of missing data, and we applied the EM algorithm for Mixture Gaussian model Keywords: expectation maximization algorithm, missing data, imputation, maximum likelihood Method