Edgeworth expansions for sampling without replacement from finite populations
The validity of the one-term Edgeworth expansion is proved for the multivariate mean of a random sample drawn without replacement under a limiting non-latticeness condition on the population. The theorem is applied to deduce the one-term expansion for the univariate statistics which can be expressed in a certain linear plus quadratic form. An application of the results to the theory of bootstrap is mentioned. A one-term expansion is also proved in the univariate lattice case.
Year of publication: |
1985
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Authors: | Babu, G. Jogesh ; Singh, Kesar |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 17.1985, 3, p. 261-278
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Publisher: |
Elsevier |
Keywords: | edgeworth expansions sampling without replacement weak convergence characteristic functions ratio estimators lattice distributions rank tests |
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