EM Algorithms from a Non-stochastic Perspective
Charles Byrne ()
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Charles Byrne: University of Massachusetts Lowell, Department of Mathematical Sciences
A chapter in Handbook of Mathematical Methods in Imaging, 2015, pp 389-429 from Springer
Abstract:
Abstract The EM algorithm is not a single algorithm, but a template for the construction of iterative algorithms. While it is always presented in stochastic language, relying on conditional expectations to obtain a method for estimating parameters in statistics, the essence of the EM algorithm is not stochastic. The conventional formulation of the EM algorithm given in many texts and papers on the subject is inadequate. A new formulation is given here based on the notion of acceptable data.
Keywords: Expectation Maximization (EM); Acceptable Data; Multiplicative Algebraic Reconstruction Technique (MART); Missing Data Models; Preference Data (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4939-0790-8_46
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DOI: 10.1007/978-1-4939-0790-8_46
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