F-tests for generalized linear hypotheses in subnormal models

João Tiago Praça Nunes Mexia, Gerberto Carvalho Dias

Research output: Contribution to journalArticlepeer-review


When the measurement errors may be assumed to be normal and independent from what is measured a subnormal model may be used. We define a linear and generalized linear hypotheses for these models, and derive F-tests for them. These tests are shown to be UMP for linear hypotheses as well as strictly unbiased and strongly consistent for these hypotheses. It is also shown that the F-tests are invariant for regular transformations, possess structural stability and are almost strongly consistent for generalized linear hypothesis. An application to a mixed model studied by Michalskyi and Zmyślony is shown.
Original languageEnglish
Pages (from-to)49-62
Number of pages14
JournalDiscussiones Mathematicae: Probability and Statistics
Issue number1
Publication statusPublished - 1 Jan 2001


  • F-tests
  • subnormal models
  • mixed models
  • invariance
  • UMP tests
  • third type error


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