A central limit theorem for self-normalized sums of a linear process

Let be a linear process, where and [var epsilon]t, t[set membership, variant]Z, are i.i.d. r.v.'s in the domain of attraction of a normal law with zero mean and possibly infinite variance. We prove a central limit theorem for self-normalized sums where is a sum of squares of block-sums of size m, as m and the number of blocks N=n/m tend to infinity.

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Year of publication:	2007
Authors:	Juodis, Mindaugas ; Rackauskas, Alfredas
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 77.2007, 15, p. 1535-1541
Publisher:	Elsevier
Subject:	Linear process Normal law Self-normalization

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005319800