Statistical Analysis of Multi-Censored Electromigration Data using the EM Algorithm

Abstract

The novelty of this work lies in using the E&M algorithm for analyzing multi-censored mixture distribution EM data. Furthermore, the Akaike Information Criterion (AIC) will be used to determine the number of failure mechanisms in a given set of failure data and the Bayes' posterior probability theory is applied to determine the probability of each failure data belonging to the different failure mechanisms. All these useful information are further validated by performing failure analysis on selected test units.