Percentage Points of the Statistics for Testing Hypotheses on Mean Vectors of Multivariate Normal Distributions with Missing Observations

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Abstract

A problem of testing of hypotheses on the mean vector of a multivariate normal distribution with unknown and positive definite covariance matrix is considered when a sample with a special, though not unusual, pattern of missing observations from that population is available. The approximate percentage points of the test statistic are obtained and their accuracy has been checked by comparing them with some exact percentage points which are calculated for complete samples and some special incomplete samples. The approximate percentage points are in good agreement with exact percentage points. The above work is extended to the problem of testing the hypothesis of equality of two mean vectors of two multivariate normal distributions with the same, unknown covariance matrix.

Original languageEnglish (US)
Pages (from-to)211-224
Number of pages14
JournalJournal of Statistical Computation and Simulation
Volume2
Issue number3
DOIs
StatePublished - Jun 1 1973

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modeling and Simulation
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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