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CENTRAL LIMIT THEOREM ON HYPERGROUPS
"... Abstract. On the basis of Heyer and Zeuner’s results we will treat the central limit theorem for probability measures on hypergroup. The purpose of this article is to verify a central limit theorem for random variables which take their values in a hypergroup. However the special case that G is the o ..."
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Abstract. On the basis of Heyer and Zeuner’s results we will treat the central limit theorem for probability measures on hypergroup. The purpose of this article is to verify a central limit theorem for random variables which take their values in a hypergroup. However the special case that G
Central Limit Theorems and Proofs
"... The following gives a selfcontained treatment of the central limit theorem (CLT). It is based on Lindeberg’s (1922) method. To state the CLT which we shall prove, we introduce the following notation. We assume that Xn1,..., Xnn are independent random variables with means 0 and respective variances ..."
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The following gives a selfcontained treatment of the central limit theorem (CLT). It is based on Lindeberg’s (1922) method. To state the CLT which we shall prove, we introduce the following notation. We assume that Xn1,..., Xnn are independent random variables with means 0 and respective variances
CENTRAL LIMIT THEOREM FOR DETERMINISTIC SYSTEMS
, 1996
"... A unified approach to obtaining the central limit theorem for hyperbolic dynamical systems is presented. It builds on previous results for one dimensional maps but it applies to the multidimensional case as well. ..."
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Cited by 76 (4 self)
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A unified approach to obtaining the central limit theorem for hyperbolic dynamical systems is presented. It builds on previous results for one dimensional maps but it applies to the multidimensional case as well.
CENTRAL LIMIT THEOREMS FOR RECORDS
"... Abstract. Consider a sequence (Xn) of independent and identically distributed random variables, taking nonnegative integer values and call Xn a record if Xn> max{X1,..., Xn−1}. In Gouet et al. (2001), a martingale approach combined with asymptotic results for sums of partial minima was used to de ..."
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to derive strong convergence results for the number of records among the first n observations. Now, in this paper we exploit the connection between records and martingales to establish a central limit theorem for the number of records in many discrete distributions, identifying the centering and scaling
GENERATING FUNCTIONS AND CENTRAL LIMIT THEOREMS
"... • Sums of independent random variables and powers of generating functions • A central limit theorem • Bivariate generating functions ..."
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• Sums of independent random variables and powers of generating functions • A central limit theorem • Bivariate generating functions
Bootstrap with . . . Central Limit Theorems.
, 1990
"... We consider "bootstrap" estimators of the distribution of the empirical process, indexed by a class offunctions F, that emerge by weighting the data by multipliers ~ / 2:]=1 Yj, for iid positive random variables, Yll Y2, ••• • Assuming that the ~'s satisfy the L2,1 integrability condi ..."
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condition fo oo Jp(IY11> t) dt < 00, we prove that FE CLT(P) and PF2: = P(suPfEFlf(x)1)2 < 00, is necessary and sufficient for the bootstrap central limit theorem to hold, almost surely, and F E CLT(P) for it to hold "in probability". These results parallel those of Cine and Zinn (1990
The Bosonic Central Limit Theorem
, 2002
"... The aim of this article is to give an overview on recent progress of the central limit theorem for mixing quantum spin chains. The limit theorem we discuss here is described in the language of operator algebras. $(\mathrm{c}.\mathrm{f} $. [4], [5] $) $ We consider the following one dimensional quant ..."
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The aim of this article is to give an overview on recent progress of the central limit theorem for mixing quantum spin chains. The limit theorem we discuss here is described in the language of operator algebras. $(\mathrm{c}.\mathrm{f} $. [4], [5] $) $ We consider the following one dimensional
Central Limit Theorem
"... fluctuationdissipation theoremNote: var[X] = σ 2 X ≡ E [ (XE[X])2] ..."
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Cited by 1 (1 self)
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fluctuationdissipation theoremNote: var[X] = σ 2 X ≡ E [ (XE[X])2]
CENTRAL LIMIT THEOREM ON CHEBYSHEV POLYNOMIALS
"... Abstract. Let Tl be a transformation on the interval [−1, 1] defined by Chebyshev polynomial of degree l (l ≥ 2), i.e., Tl(cos θ) = cos(lθ). In this paper, we consider Tl as a measure preserving transformation on [−1, 1] with an invariant measure 1 pi 1−x2 dx. We show that If f(x) is a nonconstant ..."
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step function with finite kdiscontinuity points with k < l − 1, then it satisfies the Central Limit Theorem. We also give an explicit method how to check whether it satisfies the Central Limit Theorem or not in the cases of general step functions with finite discontinuity points. 1.
) dy. Central Limit Theorem
, 2002
"... describes a “bellcurve ” centred at µ with variance σ2 (or spread σ). A random variable N is normally distributed with mean µ and variance σ2, written N (µ, σ2), if N has this density. That is, if Pr{N ≤ x} = ∫ x n(y) dy = 1 σ ..."
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describes a “bellcurve ” centred at µ with variance σ2 (or spread σ). A random variable N is normally distributed with mean µ and variance σ2, written N (µ, σ2), if N has this density. That is, if Pr{N ≤ x} = ∫ x n(y) dy = 1 σ
Results 1  10
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2,627,067