On sets of weak uniform distribution
Imre Z. Ruzsa (1989)
Colloquium Mathematicae
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Displaying similar documents to “Various limit theorems for ratios from the uniform distribution”
On sets of weak uniform distribution
Moments of order statistics of the Generalized T Distribution
Ali İ. Genç (2015)
Discussiones Mathematicae Probability and Statistics
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We derive an explicit expression for the single moments of order statistics from the generalized t (GT) distribution. We also derive an expression for the product moment of any two order statistics from the same distribution. Then the location-scale estimating problem of a real data set is solved alternatively by the best linear unbiased estimates which are based on the moments of order statistics.
An approach to generating uniform distribution
D. Pantić, N. Bijedić (1984)
Matematički Vesnik
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On weak uniform distribution of sequences of integers
E. Rosochowicz (1989)
Colloquium Mathematicae
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Limit theorems for bivariate extremes of non-identically distributed random variables
H. M. Barakat (2002)
Applicationes Mathematicae
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The limit behaviour of the extreme order statistics arising from n two-dimensional independent and non-identically distributed random vectors is investigated. Necessary and sufficient conditions for the weak convergence of the distribution function (d.f.) of the vector of extremes, as well as the form of the limit d.f.'s, are obtained. Moreover, conditions for the components of the vector of extremes to be asymptotically independent are studied.
Approximate Distributions of Order Statistics, with Applications to Nonparametric Statistics - R. D. Reiss.
L. Weiss (1991)
Metrika
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Bootstrap method for central and intermediate order statistics under power normalization
Haroon Mohamed Barakat, E. M. Nigm, O. M. Khaled (2015)
Kybernetika
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It has been known for a long time that for bootstrapping the distribution of the extremes under the traditional linear normalization of a sample consistently, the bootstrap sample size needs to be of smaller order than the original sample size. In this paper, we show that the same is true if we use the bootstrap for estimating a central, or an intermediate quantile under power normalization. A simulation study illustrates and corroborates theoretical results.
Characterizations of power distributions via moments of order statistics and record values
Z. Grudzień, D. Szynal (1999)
Applicationes Mathematicae
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Power distributions can be characterized by equalities involving three moments of order statistics. Similar equalities involving three moments of k-record values can also be used for such a characterization. The case of samples with random sizes is also considered.
Evaluations of expected generalized order statistics in various scale units
Erhard Cramer, Udo Kamps, Tomasz Rychlik (2002)
Applicationes Mathematicae
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We present sharp upper bounds for the deviations of expected generalized order statistics from the population mean in various scale units generated by central absolute moments. No restrictions are imposed on the parameters of the generalized order statistics model. The results are derived by combining the unimodality property of the uniform generalized order statistics with the Moriguti and Hölder inequalities. They generalize evaluations for specific models of ordered observations. ...
On the Distribution of Linear Functions of Spacings from a Uniform Distribution.
Lionel Weiss (1962)
Mathematica Scandinavica
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Subdiagonal and almost uniform distributions.
Ressel, Paul (2002)
Electronic Communications in Probability [electronic only]
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Goodness-of-fit tests based on characterizations in terms of moments of order statistics
K. W. Morris, D. Szynal (2002)
Applicationes Mathematicae
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Using characterization conditions of continuous distributions in terms of moments of order statistics given in [12], [23], [6] and [7] we present new goodness-of-fit techniques.
Goodness-of-fit tests using characterizations of continuous distributions
Kerwin Morris, Dominik Szynal (2001)
Applicationes Mathematicae
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Using characterization conditions of continuous distributions in terms of moments of order statistics and moments of record values we present new goodness-of-fit techniques.