Estimating the Mahalanobis distance from mixed continuous and discrete data

Edward J. Bedrick, Jodi Lapidus, Joseph F. Powell

Research output: Contribution to journalArticle

39 Citations (Scopus)

Abstract

We present a method for estimating the Mahalanobis distance between two multivariate normal populations when a subset of the measurements is observed as ordered categorical responses. Asymptotic properties of the proposed estimator are developed. Two examples are discussed.

Original languageEnglish (US)
Pages (from-to)394-401
Number of pages8
JournalBiometrics
Volume56
Issue number2
StatePublished - Jun 2000

Fingerprint

Mahalanobis Distance
Discrete Data
Normal Population
Multivariate Normal
Categorical
Asymptotic Properties
Estimator
Subset
Population
methodology

Keywords

  • Discriminant analysis
  • Distance between populations
  • Multidimensional scaling
  • Multivariate probit model

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Public Health, Environmental and Occupational Health
  • Agricultural and Biological Sciences (miscellaneous)
  • Applied Mathematics
  • Statistics and Probability

Cite this

Estimating the Mahalanobis distance from mixed continuous and discrete data. / Bedrick, Edward J.; Lapidus, Jodi; Powell, Joseph F.

In: Biometrics, Vol. 56, No. 2, 06.2000, p. 394-401.

Research output: Contribution to journalArticle

Bedrick, EJ, Lapidus, J & Powell, JF 2000, 'Estimating the Mahalanobis distance from mixed continuous and discrete data', Biometrics, vol. 56, no. 2, pp. 394-401.
Bedrick, Edward J. ; Lapidus, Jodi ; Powell, Joseph F. / Estimating the Mahalanobis distance from mixed continuous and discrete data. In: Biometrics. 2000 ; Vol. 56, No. 2. pp. 394-401.
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