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Title: SECOND-ORDER AND BOOTSTRAP APPROXIMATION TO STUDENT'S ...-STATISTIC.
Authors: Bloznelis, M., Putter, H.
Source: Theory of Probability & Its Applications. 2003, Vol. 47 Issue 2, p300. 8p.
Subjects: Edgeworth expansions, T-test (Statistics)
Abstract: We prove the validity of one-term Edgeworth expansion for Student's t-statistic under minimal conditions: the distribution of observations is nonlattice and has finite third moment. As a corollary we obtain the second-order correctness for the bootstrap of Student's t-statistic under these optimal conditions, thus extending classical result of Singh [Ann. Statist., 9 (1981), pp. 1187 1195] to the Studentized mean. [ABSTRACT FROM AUTHOR]
Copyright of Theory of Probability & Its Applications is the property of Society for Industrial & Applied Mathematics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: We prove the validity of one-term Edgeworth expansion for Student's t-statistic under minimal conditions: the distribution of observations is nonlattice and has finite third moment. As a corollary we obtain the second-order correctness for the bootstrap of Student's t-statistic under these optimal conditions, thus extending classical result of Singh [Ann. Statist., 9 (1981), pp. 1187 1195] to the Studentized mean. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Theory of Probability & Its Applications is the property of Society for Industrial & Applied Mathematics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1137/S0040585X97979743
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        Text: English
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      – SubjectFull: T-test (Statistics)
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              Text: 2003
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