{ "id": "math/0612747", "version": "v2", "published": "2006-12-24T00:31:52.000Z", "updated": "2007-12-11T14:41:05.000Z", "title": "Law of the iterated logarithm for stationary processes", "authors": [ "Ou Zhao", "Michael Woodroofe" ], "comment": "Published in at http://dx.doi.org/10.1214/009117907000000079 the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org)", "journal": "Annals of Probability 2008, Vol. 36, No. 1, 127-142", "doi": "10.1214/009117907000000079", "categories": [ "math.PR" ], "abstract": "There has been recent interest in the conditional central limit question for (strictly) stationary, ergodic processes $...,X_{-1},X_0,X_1,...$ whose partial sums $S_n=X_1+...+X_n$ are of the form $S_n=M_n+R_n$, where $M_n$ is a square integrable martingale with stationary increments and $R_n$ is a remainder term for which $E(R_n^2)=o(n)$. Here we explore the law of the iterated logarithm (LIL) for the same class of processes. Letting $\\Vert\\cdot\\Vert$ denote the norm in $L^2(P)$, a sufficient condition for the partial sums of a stationary process to have the form $S_n=M_n+R_n$ is that $n^{-3/2}\\Vert E(S_n|X_0,X_{-1},...)\\Vert$ be summable. A sufficient condition for the LIL is only slightly stronger, requiring $n^{-3/2}\\log^{3/2}(n)\\Vert E(S_n|X_0,X_{-1},...)\\Vert$ to be summable. As a by-product of our main result, we obtain an improved statement of the conditional central limit theorem. Invariance principles are obtained as well.", "revisions": [ { "version": "v2", "updated": "2007-12-11T14:41:05.000Z" } ], "analyses": { "subjects": [ "60F15", "60F05" ], "keywords": [ "iterated logarithm", "stationary processes", "sufficient condition", "conditional central limit theorem", "partial sums" ], "tags": [ "journal article" ], "note": { "typesetting": "TeX", "pages": 0, "language": "en", "license": "arXiv", "status": "editable", "adsabs": "2006math.....12747Z" } } }