Estimation of Parameters for a Mixture of Normal Distributions

Published

Journal Article

In observations are taken from a mixture of K normal subpopulations, where the value of K is known. It is assumed that these n observations are given as N frequencies from equally spaced intervals. Initial guesses of the K means, K variances, and K − 1 proportions are made using the maximum likelihood estimates for a single truncated normal population as derived by Hald. Then an approximation to the likelihood function of the entire sample is used, and attempts to maximize this yield two iteration formulas. In practice, the method of steepest descent always converged, although the rate was not always fast. Special cases of equal variances and variances proportional to the square of the mean are also considered. © 1966 Taylor & Francis Group, LLC.

Full Text

Duke Authors

Cited Authors

  • Hasselblad, V

Published Date

  • January 1, 1966

Published In

Volume / Issue

  • 8 / 3

Start / End Page

  • 431 - 444

Electronic International Standard Serial Number (EISSN)

  • 1537-2723

International Standard Serial Number (ISSN)

  • 0040-1706

Digital Object Identifier (DOI)

  • 10.1080/00401706.1966.10490375

Citation Source

  • Scopus