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Generalized p value for multivariate Gaussian stochastic processes in continuous time

Author

Listed:
  • Mar Fenoy

    (Universidad Complutense de Madrid)

  • Pilar Ibarrola

    (Universidad Complutense de Madrid)

  • Juan B. Seoane-Sepúlveda

    (Universidad Complutense de Madrid)

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.

Suggested Citation

  • Mar Fenoy & Pilar Ibarrola & Juan B. Seoane-Sepúlveda, 2019. "Generalized p value for multivariate Gaussian stochastic processes in continuous time," Statistical Papers, Springer, vol. 60(6), pages 2013-2030, December.
    • Handle: RePEc:spr:stpapr:v:60:y:2019:i:6:d:10.1007_s00362-017-0907-7
    DOI: 10.1007/s00362-017-0907-7
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    References listed on IDEAS

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    1. Masafumi Akahira, 2002. "Confidence intervals for the difference of means: application to the Behrens-Fisher type problem," Statistical Papers, Springer, vol. 43(2), pages 273-284, April.
    2. Gamage, Jinadasa & Mathew, Thomas & Weerahandi, Samaradasa, 2004. "Generalized p-values and generalized confidence regions for the multivariate Behrens-Fisher problem and MANOVA," Journal of Multivariate Analysis, Elsevier, vol. 88(1), pages 177-189, January.
    3. Sevil Bacanli & Yaprak Demirhan, 2008. "A group sequential test for the inverse Gaussian mean," Statistical Papers, Springer, vol. 49(2), pages 377-386, April.
    4. M. Salau, 2003. "The effects of different choices of order for autoregressive approximation on the Gaussian likelihood estimates for ARMA models," Statistical Papers, Springer, vol. 44(1), pages 89-105, January.
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