A Note on Computing Extreme Tail Probabilities of the Noncentral $t$-Distribution with Large Noncentrality Parameter

Viktor Witkovský

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Algorithm 93. Non-central F or beta distribution

I. Siatkowski (1988)

Applicationes Mathematicae

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$k$ -Depth-nearest Neighbour Method and its Performance on Skew-normal Distributons

Ondřej Vencálek (2013)

Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica

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In the present paper we investigate performance of the $k$ -depth-nearest classifier. This classifier, proposed recently by Vencálek, uses the concept of data depth to improve the classification method known as the $k$ -nearest neighbour. Simulation study which is presented here deals with the two-class classification problem in which the considered distributions belong to the family of skewed normal distributions.

A note concerning the limit distribution of the quicksort algorithm

Michael Cramer (1996)

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Conditional problem for objective probability

Otakar Kříž (1998)

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Marginal problem (see [Kel]) consists in finding a joint distribution whose marginals are equal to the given less-dimensional distributions. Let’s generalize the problem so that there are given not only less-dimensional distributions but also conditional probabilities. It is necessary to distinguish between objective (Kolmogorov) probability and subjective (de Finetti) approach ([Col,Sco]). In the latter, the coherence problem incorporates both probabilities and conditional probabilities...

Histogram analysis by use of L-moments, linear functions of order statistics

Martial Guillaud, Jean-Marc Chassery (1991)

Statistique et analyse des données

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Displaying similar documents to “A Note on Computing Extreme Tail Probabilities of the Noncentral t -Distribution with Large Noncentrality Parameter”

Algorithm 93. Non-central F or beta distribution

k -Depth-nearest Neighbour Method and its Performance on Skew-normal Distributons

A note concerning the limit distribution of the quicksort algorithm

Conditional problem for objective probability

Histogram analysis by use of L-moments, linear functions of order statistics

Displaying similar documents to “A Note on Computing Extreme Tail Probabilities of the Noncentral $t$ -Distribution with Large Noncentrality Parameter”

$k$ -Depth-nearest Neighbour Method and its Performance on Skew-normal Distributons