EM Algorithm
نویسندگان
چکیده
It’s very important for us to understand the data structure before doing the data analysis. However, most of the time, there may exist of a lot of missing values or incomplete information in the data subject to the analysis. For example, survival time data always have some missing values because of death or job transfer. These kinds of data are called censored data. Since these data might obtain some incomplete but useful information, if we ignore them in the analysis, it’s risky for us to get some biased results. The EM algorithm has the ability to deal with missing data and unidentified variables, so it is becoming useful in a variety of incomplete-data problem.
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