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Statistical Papers

, Volume 60, Issue 6, pp 2013–2030 | Cite as

Generalized p value for multivariate Gaussian stochastic processes in continuous time

  • Mar FenoyEmail author
  • Pilar Ibarrola
  • Juan B. Seoane-Sepúlveda
Regular Article
  • 95 Downloads

Abstract

We construct a Generalized p value for testing statistical hypotheses on the comparison of mean vectors in the sequential observation of two continuous time multidimensional Gaussian processes. The mean vectors depend linearly on two multidimensional parameters and with different conditions about their covariance structures. The invariance of the generalized p value considered is proved under certain linear transformations. We report results of a simulation study showing power and errors probabilities for them. Finally, we apply our results to a real data set.

Keywords

Generalized p value Hypothesis testing Continuous time Multivariate Behrens–Fisher problem 

Mathematics Subject Classification

Primary: 62M09 Secondary: 62H12 

Notes

Acknowledgements

The authors thank the anonymous referees for their helpful comments and suggestions. The first and third authors were supported by MTM2015-65825-P

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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • Mar Fenoy
    • 1
    Email author
  • Pilar Ibarrola
    • 1
  • Juan B. Seoane-Sepúlveda
    • 2
  1. 1.Departamento de Estadística e Investigación Operativa, Facultad de Ciencias MatemáticasUniversidad Complutense de MadridMadridSpain
  2. 2.Departamento de Análisis Matemático, Facultad de Ciencias Matemáticas, Instituto de Matemática Interdisciplinar (IMI)Universidad Complutense de MadridMadridSpain

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