M. Cramer and L. Ruschendorf, Analysis of recursive algorithms by the contraction method, in Athens Conference on Applied Probability and Time Series Analysis, Athens, Greece, 1995.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....necessitates the use of a probability metric that is ideal of order larger than two as well as information on the variance. In either case a feature of the contraction method is that the dependence between T n and I n can be succinctly handled. For other applications of the contraction method, see [16, 49, 51, 55]. The method of moments, one of the most classical ways of deriving limit distributions, has been widely applied to problems in diverse elds (see for example Billingsley [8, Section 30] Diaconis [20] It consists in rst computing the mean and variance, scaling properly the random variable, ....

M. Cramer and L. Ruschendorf, Analysis of recursive algorithms by the contraction method, in Athens Conference on Applied Probability and Time Series Analysis, Athens, Greece, 1995.

....necessitates the use of a probability metric that is ideal of order larger than two as well as information on the variance. In either case a feature of the contraction method is that the dependence between T n and I n can be succinctly handled. For other applications of the contraction method, see [16, 49, 51, 55]. The method of moments, one of the most classical ways of deriving limit distributions, has been widely applied to problems in diverse fields (see for example Billingsley [8, Section 30] Diaconis [20] It consists in first computing the mean and variance, scaling properly the random variable, ....

M. Cramer and L. Ruschendorf, Analysis of recursive algorithms by the contraction method, in Athens Conference on Applied Probability and Time Series Analysis, Athens, Greece, 1995.

....necessitates the use of a probability metric that is ideal of order larger than two as well as information on the variance. In either case a feature of the contraction method is that the dependence between T n and I n can be succinctly handled. For other applications of the contraction method, see [48, 15, 50]. The method of moments, one of the most classical ways of deriving limit distributions, has been widely applied to problems in diverse elds (see for example Billingsley [8, Section 30] Diaconis [19] It consists in rst computing the mean and variance, scaling properly the random variable, ....

M. Cramer and L. Ruschendorf, Analysis of recursive algorithms by the contraction method, in Athens Conference on Applied Probability and Time Series Analysis, Athens, Greece,

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