Results 1 to 10 of about 11,862,847 (308)
Order Statistics and Benford′s Law [PDF]
Fix a baseB> 1 and letζhave the standard exponential distribution; the distribution of digits ofζbaseBis known to be very close to Benford′s law. If there exists aCsuch that the distribution of digits ofCtimes the elements of some set is the same as that ofζ, we say that set exhibits shifted exponential behavior baseB.LetX1, …,XNbe i.i.d.r.v.
Steven J. Miller, Mark J. Nigrini
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Sequential order statistics with an order statistics prior
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Marco Burkschat, Udo Kamps, Maria Kateri
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Conditional ordering of order statistics
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Weiwei Zhuang, Junchao Yao, Taizhong Hu
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Spacings around an order statistic [PDF]
We determine the joint limiting distribution of adjacent spacings around a central, intermediate, or an extreme order statistic $X_{k:n}$ of a random sample of size $n$ from a continuous distribution $F$. For central and intermediate cases, normalized spacings in the left and right neighborhoods are asymptotically i.i.d.
Nagaraja, H. N. +2 more
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Expected values and standard deviations of order statistics from a logistic distribution are given for sample sizes $n = 1,2, \cdots, 10$ and $n = 15, 20, 50$, and 100, and summarized in graphs to facilitate interpolation to other sample sizes. For $n \leqq 10$ the results are compared with asymptotic approximations.
Birnbaum, Allan, Dudman, Jack
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Independence of Order Statistics
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Falk, M., Reiss, R.-D.
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Building on the notion of $q$-integral introduced by Thomae in 1869, we introduce $q$-order statistics (that, is $q$-analogues of the classical order statistics, for ...
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On the Completeness of Order Statistics
Let $X_1, X_2, \cdots, X_n$ be a sample of a one-dimensional random variable $X$; let the order statistic $T(X_1, X_2, \cdots, X_n)$ be defined in such a manner that $T(x_1, x_2, \cdots, x_n) = (x^{(1)}, x^{(2)}, \cdots, x^{(n)})$ where $x^{(1)} \leqq x^{(2)} \leqq \cdots \leqq x^{(n)}$ denote the ordered $x's$; and let $\Omega$ be a class of one ...
Bell, C. B. +2 more
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Let $X_{(i\mid n)}$ be the $i$th smallest order statistic from a population with $\operatorname{pdf} f(x)$ and $\operatorname{cdf} F(x)$. When $\tilde{x}$ is the population median, $n$ is the sample size and $G(x) = F(x)(1 - F(x))$, the following are proved.
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Order Statistics in Artificial Evolution [PDF]
This article deals with the exploitation of statistical information from extremes values of an evolutionary algorithm. One can use the fact that upper order statistics of a sample converge to known distributions for improving efficiency of selection and crossover operators.
Puechmorel, Stéphane, Delahaye, Daniel
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