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Volumn , Issue , 2009, Pages 25-51

A review of multivariate theory for high dimensional data with fewer observations

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EID: 79954860307     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1142/9789812838247_0002     Document Type: Chapter
Times cited : (5)

References (25)
  • 1
    • 2142645905 scopus 로고    scopus 로고
    • Effect of high dimension: By an example of a two sample problem
    • Bai, Z. and Saranadasa, H. (1996). Effect of high dimension: by an example of a two sample problem. Statistica Sinica., 6, 311-329.
    • (1996) Statistica Sinica. , vol.6 , pp. 311-329
    • Bai, Z.1    Saranadasa, H.2
  • 2
    • 0001677717 scopus 로고
    • Controlling the false discovery rate: A practical and powerful approach to multiple testing
    • Benjamini, Y. and Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. Roy. Statist. Soc., B 57, 289-300.
    • (1995) J. Roy. Statist. Soc., B , vol.57 , pp. 289-300
    • Benjamini, Y.1    Hochberg, Y.2
  • 3
    • 0035733108 scopus 로고    scopus 로고
    • The control of the false discovery rate in multiple testing under dependency
    • Benjamini, Y. and Yekuteli, D. (2001). The control of the false discovery rate in multiple testing under dependency. Ann. Statist., 29, 1165-1181.
    • (2001) Ann. Statist. , vol.29 , pp. 1165-1181
    • Benjamini, Y.1    Yekuteli, D.2
  • 4
    • 0043114430 scopus 로고
    • A high dimensional two sample significance test.Ann
    • Dempster, A.P. (1958). A high dimensional two sample significance test.Ann. Math. Stat., 29, 995-1010.
    • (1958) Math. Stat. , vol.29 , pp. 995-1010
    • Dempster, A.P.1
  • 5
    • 0041611615 scopus 로고
    • A significance test for the separation of two highly multivariate small samples
    • Dempster, A.P. (1960). A significance test for the separation of two highly multivariate small samples. Biometrics, 16, 41-50.
    • (1960) Biometrics , vol.16 , pp. 41-50
    • Dempster, A.P.1
  • 6
    • 33748428804 scopus 로고    scopus 로고
    • Multivariate analysis for the case when the dimension is large compared to the sample size
    • Fujikoshi, Y. (2004) Multivariate analysis for the case when the dimension is large compared to the sample size. J. Korean Statist. Soc., 33, 1-24.
    • (2004) J. Korean Statist. Soc. , vol.33 , pp. 1-24
    • Fujikoshi, Y.1
  • 7
    • 33748425493 scopus 로고    scopus 로고
    • Asymptotic results of a high dimensional MANOVA test and power comparison when the dimension is large compared to the sample size
    • Fujikoshi, Y., Himeno, T. and Wakaki, H. (2004). Asymptotic results of a high dimensional MANOVA test and power comparison when the dimension is large compared to the sample size. J. Japan Statist. Soc., 34, 19-26.
    • (2004) J. Japan Statist. Soc. , vol.34 , pp. 19-26
    • Fujikoshi, Y.1    Himeno, T.2    Wakaki, H.3
  • 8
    • 52749099161 scopus 로고    scopus 로고
    • Estimation of the precision matrix of a singularWishart distribution and its application in high dimensional data
    • Kubokawa, T. and Srivastava, M.S. (2008). Estimation of the precision matrix of a singularWishart distribution and its application in high dimensional data. J. Multivariate Analy, 99, 1906-1928.
    • (2008) J. Multivariate Analy , vol.99 , pp. 1906-1928
    • Kubokawa, T.1    Srivastava, M.S.2
  • 9
    • 0036392431 scopus 로고    scopus 로고
    • Some hypothesis tests for the covariance matrix when the dimension is large compared to the sample size
    • Ledoit, O., andWolf, M. (2002).Some hypothesis tests for the covariance matrix when the dimension is large compared to the sample size. Ann. Statist., 30, 1081-1102.
    • (2002) Ann. Statist. , vol.30 , pp. 1081-1102
    • Ledoit, O.1    Wolf, M.2
  • 12
    • 38249000990 scopus 로고
    • Asymptotic expansion of the misclassification probabilities of Dand Acriteria for discrimination from two high-dimensional populations using the theory of large-dimensional random matrices
    • Saranadosa, H. (1993). Asymptotic expansion of the misclassification probabilities of Dand Acriteria for discrimination from two high-dimensional populations using the theory of large-dimensional random matrices J. Multivariate Analy., 46, 154-174.
    • (1993) J. Multivariate Analy. , vol.46 , pp. 154-174
    • Saranadosa, H.1
  • 13
    • 1442307325 scopus 로고
    • On an optimum property of two important statistical tests
    • Simaika, J. B. (1941). On an optimum property of two important statistical tests. Biometrika, 32, 70-80.
    • (1941) Biometrika , vol.32 , pp. 70-80
    • Simaika, J.B.1
  • 14
    • 33748424308 scopus 로고    scopus 로고
    • Multivariate theory for analyzing high dimensional data
    • Srivastava, M.S. (2007). Multivariate theory for analyzing high dimensional data. J. Japan Stat. Soc., 37, 53-86.
    • (2007) J. Japan Stat. Soc. , vol.37 , pp. 53-86
    • Srivastava, M.S.1
  • 15
    • 33748439503 scopus 로고    scopus 로고
    • Minimum distance classification rules for high dimensional data
    • Srivastava, M.S. (2006a). Minimum distance classification rules for high dimensional data. J. Multivariate Analy., 97, 2057-2070
    • (2006) J. Multivariate Analy. , vol.97 , pp. 2057-2070
    • Srivastava, M.S.1
  • 17
    • 33748417779 scopus 로고    scopus 로고
    • Some tests concerning the covariance matrix in highdimensional data
    • Srivastava, M.S. (2005). Some tests concerning the covariance matrix in highdimensional data. J. Japan Stat. Soc., 35, 251-272.
    • (2005) J. Japan Stat. Soc. , vol.35 , pp. 251-272
    • Srivastava, M.S.1
  • 18
    • 0242511222 scopus 로고    scopus 로고
    • Singular Wishart and Multivariate beta distributions
    • Srivastava, M.S. (2003). Singular Wishart and Multivariate beta distributions. Ann. Statist., 31, 1537-1560.
    • (2003) Ann. Statist. , vol.31 , pp. 1537-1560
    • Srivastava, M.S.1
  • 19
    • 51249190323 scopus 로고
    • Asymptotically most powerful rank tests for regression parameters in MANOVA
    • Srivastava, M.S. (1972). Asymptotically most powerful rank tests for regression parameters in MANOVA. Ann. Inst. Math. Statist., 24, 285-297.
    • (1972) Ann. Inst. Math. Statist. , vol.24 , pp. 285-297
    • Srivastava, M.S.1
  • 20
    • 38349143210 scopus 로고
    • On a class of nonparametric tests for regression parameters
    • Srivastava, M.S. (1968). On a class of nonparametric tests for regression parameters. Ann. Math. Statist.(Abstract), 39, 697.
    • (1968) Ann. Math. Statist.(Abstract) , vol.39 , pp. 697
    • Srivastava, M.S.1
  • 22
    • 38349085267 scopus 로고    scopus 로고
    • A test for the mean vector with fewer observations than the dimension
    • Srivastava, M.S. and Du, M (2008). A test for the mean vector with fewer observations than the dimension. Jour. Multivariate Analys., 99, 386-402.
    • (2008) Jour. Multivariate Analys. , vol.99 , pp. 386-402
    • Srivastava, M.S.1    Du, M.2
  • 23
    • 33748413613 scopus 로고    scopus 로고
    • Multivariate analysis of variance with fewer observations than the dimension
    • Srivastava, M.S. and Fujikoshi, Y. (2006). Multivariate analysis of variance with fewer observations than the dimension. J. Multivariate Analy., 97, 1927-1940.
    • (2006) J. Multivariate Analy. , vol.97 , pp. 1927-1940
    • Srivastava, M.S.1    Fujikoshi, Y.2
  • 24
    • 36549089901 scopus 로고    scopus 로고
    • Comparison of discriminant methods for high dimensional data
    • Srivastava, M.S. and Kubokawa, T. (2007). Comparison of discriminant methods for high dimensional data. J. Japan Stat. Soc., 37, 123-134.
    • (2007) J. Japan Stat. Soc. , vol.37 , pp. 123-134
    • Srivastava, M.S.1    Kubokawa, T.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.