Mixture Models; Gaussian

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a mixture model is a probabilistic model for representing the presence of subpopulations within an overall population, without requiring that an observed data set should identify the sub-population to which an individual observation belongs. The following are examples described in Wikipedia:

  1. A financial model
  2. House prices
  3. Topics in a document
  4. Handwriting recognition
  5. Assessing projectile accuracy (a.k.a. circular error probable, CEP)
  6. Direct and indirect applications
  7. Predictive Maintenance
  8. Fuzzy image segmentation

Parameter estimation and system identification

  1. Expectation maximization (EM)
  2. Markov chain Monte Carlo
  3. Moment matching
  4. Spectral method
  5. Graphical Methods
  6. Other methods
  7. A simulation