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

Mindaugas Juodis () and Alfredas Rackauskas

Statistics & Probability Letters, 2007, vol. 77, issue 15, 1535-1541

Abstract: 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.

Keywords: Linear; process; Normal; law; Self-normalization (search for similar items in EconPapers)
Date: 2007
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