A local limit theorem for sums of dependent random variables
A local version of the central limit theorem is established for normalized sums of dependent random variables when a global theorem is known and conditional distributions are sufficiently smooth. The proof uses ideas from Statistics, by representing the density as the integral of a score function for a translation family of distributions.
Year of publication: |
1990
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Authors: | Wang, Mei ; Woodroofe, Michael |
Published in: |
Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 9.1990, 3, p. 207-213
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Publisher: |
Elsevier |
Keywords: | Central limit theorem almost differentiability score function martingales stationary sequences Markov chains |
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