On classification of multiple observations with application to marketing analysis

T. P. Logan, A. K. Gupta, Jie Chen

Research output: Contribution to journalArticle

Abstract

In this paper, we study the likelihood procedure test (LPT) criterion for classification of the two-group multiple observations model, and derive the criterion under different parametric assumptions. A real life marketing data analysis is presented for illustrating the classification method introduced in this paper. It turns out that the LPT method is a useful alternative method in classification of multiple observations model.

Original languageEnglish (US)
Pages (from-to)387-402
Number of pages16
JournalAmerican Journal of Mathematical and Management Sciences
Volume20
Issue number3-4
DOIs
StatePublished - Jan 1 2000
Externally publishedYes

Fingerprint

Marketing
Likelihood
Data analysis
Alternatives
Model
Observation
Life
Test methods

Keywords

  • Hierarchical model
  • Likelihood procedure
  • Multivariate normal distribution
  • Null distribution

ASJC Scopus subject areas

  • Business, Management and Accounting(all)
  • Applied Mathematics

Cite this

On classification of multiple observations with application to marketing analysis. / Logan, T. P.; Gupta, A. K.; Chen, Jie.

In: American Journal of Mathematical and Management Sciences, Vol. 20, No. 3-4, 01.01.2000, p. 387-402.

Research output: Contribution to journalArticle

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