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American Journal of Mathematical and Management Sciences Volume 36, 2017 - Issue 1
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Original Articles

Tests for Normal Mean Vectors with Monotone Incomplete Data

Ayaka YagiTokyo University of Science, Department of Mathematical Information Science, Shinjuku-ku, Tokyo, Japan
&
Takashi SeoTokyo University of Science, Department of Mathematical Information Science, Shinjuku-ku, Tokyo, JapanCorrespondence[email protected]
Pages 1-20 | Published online: 11 Nov 2016

References

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  • Chang, W.-Y., & Richards, D. St. P. (2009). Finite-sample inference with monotone incomplete multivariate normal data, I. Journal of Multivariate Analysis, 100(9), 1883–1899.
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  • Seko, N., Yamazaki, A., & Seo, T. (2012). Tests for mean vector with two-step monotone missing data. SUT Journal of Mathematics, 48(1), 13–36.
  • Seo, T., Mano, S., & Fujikoshi, Y. (1994). A generalized Tukey conjecture for multiple comparisons among mean vectors. Journal of the American Statistical Association, 89(426), 676–679.
  • Seo, T., & Siotani, M. (1992). The multivariate Studentized range and its upper percentiles. Journal of the Japan Statistical Society, 22(2), 123–137.
  • Yagi, A., & Seo, T. (2014). A test for mean vector and simultaneous confidence intervals with three-step monotone missing data. American Journal of Mathematical and Management Sciences, 33(3), 161–175.
  • Yagi, A., & Seo, T. (2015a). Tests for mean vectors with two-step and three-step monotone samples. Josai Mathematical Monographs, 8, 49–71.
  • Yagi, A., & Seo, T. (2015b). Tests for equality of mean vectors and simultaneous confidence intervals with two-step or three-step monotone missing data patterns. American Journal of Mathematical and Management Sciences, 34(3), 213–233.
  • Yu, J., Krishnamoorthy, K., & Pannala, K. M. (2006). Two-sample inference for normal mean vectors based on monotone missing data. Journal of Multivariate Analysis, 97(10), 2162–2176.

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