Displaying similar documents to “Central limit theorem for Gibbsian U-statistics of facet processes”

Five Turning Points in the Historical Progress of Statistics - My Personal Vision

von Collani, Elart (2014)

Serdica Journal of Computing

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Statistics has penetrated almost all branches of science and all areas of human endeavor. At the same time, statistics is not only misunderstood, misused and abused to a frightening extent, but it is also often much disliked by students in colleges and universities. This lecture discusses/covers/addresses the historical development of statistics, aiming at identifying the most important turning points that led to the present state of statistics and at answering the questions “What went...

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.

A note on order statistics from symmetrically distributed samples

Marek Kałuszka, Andrzej Okolewski (2011)

Applicationes Mathematicae

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We present a first moment distribution-free bound on expected values of L-statistics as well as properties of some numerical characteristics of order statistics, in the case when the observations are possibly dependent symmetrically distributed about the common mean. An actuarial interpretation of the presented bound is indicated.

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. ...