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Book Chapter

The EM Algorithm

  • Ng S
  • Krishnan T
  • McLachlan G
Springer Berlin Heidelberg, (2012), 139-172
DOI: 10.1007/978-3-642-21551-3_6
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Abstract

In the previous set of notes, we talked about the EM algorithm as applied to fitting a mixture of Gaussians. In this set of notes, we give a broader view of the EM algorithm, and show how it can be applied to a large family of estimation problems with latent variables. We begin our discussion with a very useful result called Jensen's inequality

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APA

Ng, S. K., Krishnan, T., & McLachlan, G. J. (2012). The EM Algorithm. In Handbook of Computational Statistics (pp. 139–172). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-21551-3_6

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