Journal of Statistical Theory and Applications (JSTA) (Sep 2020)

Deriving Mixture Distributions Through Moment-Generating Functions

  • Subhash Bagui,
  • Jia Liu,
  • Shen Zhang

DOI
https://doi.org/10.2991/jsta.d.200826.001
Journal volume & issue
Vol. 19, no. 3

Abstract

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This article aims to make use of moment-generating functions (mgfs) to derive the density of mixture distributions from hierarchical models. When the mgf of a mixture distribution doesn't exist, one can extend the approach to characteristic functions to derive the mixture density. This article uses a result given by E.R. Villa, L.A. Escobar, Am. Stat. 60 (2006), 75–80. The present work complements E.R. Villa, L.A. Escobar, Am. Stat. 60 (2006), 75–80 article with many new examples.

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