Derivative domain fitting: A new method for resolving a mixture of normal distributions in the presence of a contaminating background

Dan H. Moore, Joe W. Gray

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

Derivative domain least squares analysis is a new method for resolving multiple peaks superimposed on a slowly varying continuum into separate normal (Gaussian) distributions without developing a functional approximation for the continuum. The method is based on fitting the first derivative of the data with the first derivative of the sum of a series of normal distributions. A functional approximation for the continuum is not necessary as long as the first derivative of the continuum is approximately zero (i.e., the continuum varies slowly compared to the normal distributions). © 1993 Wiley‐Liss, Inc.

Original languageEnglish (US)
Pages (from-to)510-518
Number of pages9
JournalCytometry
Volume14
Issue number5
DOIs
StatePublished - 1993

Keywords

  • Normal mixture decomposition
  • background continuum
  • bivariate distributions
  • chromosomes
  • flow karyotype

ASJC Scopus subject areas

  • Pathology and Forensic Medicine
  • Biophysics
  • Hematology
  • Endocrinology
  • Cell Biology

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