An L1-convergence theorem for heterogeneous mixingale arrays with trending moments
AbstractThis paper gives a generalization of an L1-convergence theorem for dependent processes due to Andrews (1988). Among the cases covered by this result are weak laws of large numbers for random sequences (Xt) having moments tending to either infinity or zero as t --> [infinity].
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Bibliographic InfoArticle provided by Elsevier in its journal Statistics & Probability Letters.
Volume (Year): 16 (1993)
Issue (Month): 4 (March)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
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- Hill, Jonathan B., 2010.
"On Tail Index Estimation For Dependent, Heterogeneous Data,"
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- Jonathan B. Hill, 2005. "On Tail Index Estimation for Dependent, Heterogenous Data," Econometrics 0505005, EconWPA, revised 27 May 2005.
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- Calhoun, Gray, 2013. "Block Bootstrap Consistency Under Weak Assumptions," Staff General Research Papers 34313, Iowa State University, Department of Economics.
- Jonathan B. Hill, 2005. "On Tail Index Estimation Using Dependent,Heterogenous Data," Working Papers 0512, Florida International University, Department of Economics.
- Jenish, Nazgul & Prucha, Ingmar R., 2012. "On spatial processes and asymptotic inference under near-epoch dependence," Journal of Econometrics, Elsevier, vol. 170(1), pages 178-190.
- de Jong, Robert M., 1996. "A strong law of large numbers for triangular mixingale arrays," Statistics & Probability Letters, Elsevier, vol. 27(1), pages 1-9, March.
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