Kurtosis tests for multivariate normality with monotone incomplete data

Tomoya Yamada, Megan M. Romer, Donald Richards

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

We consider the problem of testing multivariate normality when the data consist of a random sample of two-step monotone incomplete observations. We define for such data a generalization of Mardia’s statistic for measuring kurtosis, derive the asymptotic non-null distribution of the statistic under certain regularity conditions and against a broad class of alternatives, and provide an application to a well-known data set on cholesterol measurements.

Original languageEnglish (US)
Pages (from-to)532-557
Number of pages26
JournalTest
Volume24
Issue number3
DOIs
StatePublished - Sep 10 2015

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Multivariate Normality
Incomplete Data
Kurtosis
Monotone
Statistic
Cholesterol
Regularity Conditions
Testing
Alternatives
Normality
Incomplete data
Statistics
Regularity

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Cite this

Yamada, Tomoya ; Romer, Megan M. ; Richards, Donald. / Kurtosis tests for multivariate normality with monotone incomplete data. In: Test. 2015 ; Vol. 24, No. 3. pp. 532-557.
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Kurtosis tests for multivariate normality with monotone incomplete data. / Yamada, Tomoya; Romer, Megan M.; Richards, Donald.

In: Test, Vol. 24, No. 3, 10.09.2015, p. 532-557.

Research output: Contribution to journalArticle

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