SAGE Research Methods - Encyclopedia of Measurement and Statistics

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EM Algorithm

In: Encyclopedia of Measurement and Statistics
Edited by: Neil J. Salkind

One central goal of statistical inference is to estimate parameters of a model. In a typical statistical analysis, a likelihood function, L(data;θ), is used to describe the relationship between the data and some unknown parameters θ that ...

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  Salkind, N. J. (2007). Em algorithm. In Encyclopedia of measurement and statistics (pp. 311-313). Sage Publications, Inc., https://dx.doi.org/10.4135/9781412952644.n152
  
  Salkind, Neil J. "EM Algorithm." In Encyclopedia of Measurement and Statistics, edited by Salkind, Neil J., 311-13. Thousand Oaks, CA: Sage Publications, Inc., 2007. https://dx.doi.org/10.4135/9781412952644.n152.
  
  Salkind, N. J. 2007. EM Algorithm. In: Neil J. Salkind Editor, 2007. Encyclopedia of Measurement and Statistics, Thousand Oaks, CA: Sage Publications, Inc. pp. 311-313 Available at: <https://dx.doi.org/10.4135/9781412952644.n152> [Accessed 30 Jun 2022].
  
  Salkind, Neil J. "EM Algorithm." Encyclopedia of Measurement and Statistics. Edited by Thousand Oaks: Sage Publications, Inc., 2007, pp. 311-13. SAGE Research Methods. 30 Jun 2022, doi: https://dx.doi.org/10.4135/9781412952644.n152.
  
  Salkind, Neil J. (2007). Em algorithm In:EM algorithm Encyclopedia of measurement and statistics Thousand Oaks, CA: Sage Publications, Inc.; 2007:311-313. doi:10.4135/9781412952644.n152
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