Discrete approximations of continuous probability distributions obtained by minimizing Cramér-von Mises-type distances

We consider the problem of approximating a continuous random variable, characterized by a cumulative distribution function (cdf) F ( x ), by means of k points, x 1 < x 2 < ⋯ < x k , with probabilities p i , i = 1 , ⋯ , k . For a given k , a criterion for determining the x i and p i of the a...

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Bibliographic Details
Published in:	Statistical papers (Berlin, Germany) Vol. 64; no. 5; pp. 1669 - 1697
Main Authors:	Barbiero, Alessandro, Hitaj, Asmerilda
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2023 Springer Nature B.V
Subjects:	Approximation Continuity (mathematics) Distribution functions Economic Theory/Quantitative Economics/Mathematical Methods Economics Exact solutions Finance Insurance Iterative methods Management Mathematics and Statistics Operations Research/Decision Theory Probability density functions Probability Theory and Stochastic Processes Random variables Regular Article Statistics Statistics for Business Weighting functions Quantization Statistical distance Moment matching 62E15 Quantile function Cumulative distribution function 62E17
ISSN:	0932-5026, 1613-9798
Online Access:	Get full text
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