Detection of a random alteration in a multivariate observation when knowing probable direction

Barry Katz, Morton B. Brown

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

An observation from a multivariate distribution may be subject to perturbation in a known subset of the variables. A likelihood radio statistic is developed to test whether or not there has been an addition of a random quantity in a prespecified direction to an observation from a multivariate normal distribution. When the variance of this addition is unknown, a secondarily Bayes approach is used to eliminate this variance which acts as a nuisance parameter. The testing procedure is based on a distribution-free tolerance interval.

Original languageEnglish
Pages (from-to)145-155
Number of pages11
JournalComputational Statistics and Data Analysis
Volume6
Issue number2
DOIs
StatePublished - 1988

Fingerprint

Normal distribution
Probable
Set theory
Statistics
Tolerance Interval
Multivariate Normal Distribution
Distribution-free
Nuisance Parameter
Multivariate Distribution
Testing
Bayes
Statistic
Likelihood
Eliminate
Perturbation
Unknown
Subset
Observation
Nuisance parameter
Multivariate distribution

Keywords

  • Outlier detection
  • Quality control
  • Random shift in location
  • Secondarily Bayes approach

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Statistics, Probability and Uncertainty
  • Electrical and Electronic Engineering
  • Computational Mathematics
  • Numerical Analysis
  • Statistics and Probability

Cite this

Detection of a random alteration in a multivariate observation when knowing probable direction. / Katz, Barry; Brown, Morton B.

In: Computational Statistics and Data Analysis, Vol. 6, No. 2, 1988, p. 145-155.

Research output: Contribution to journalArticle

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