The Methods of Distances in the Theory of Probability and Statistics
This book covers the method of metric distances and its application in probability theory and other fields. The method is fundamental in the study of limit. This book covers the method of metric distances and its application in probability theory and other fields. The method is fundamental in the.
Applications of ideal metrics for sums of i. How close are the individual and collective models in risk theory? There are no comments yet.
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A metric on a set X is a function called the distance function or simply distance. Help with accessing the online library, referencing and using libraries near you:. Yes , it was. Observational study Natural experiment Quasi-experiment. Articles lacking in-text citations from February All articles lacking in-text citations Articles needing additional references from February All articles needing additional references. Again, a measure of distance between random variables may relate to the extent of dependence between them, rather than to their individual values.
Definitions Primary, simple and compound probability distances, and minimal and maximal distances and norms A structural classification of probability distances. Relations between compound and primary distances Moment distances Uniformity in weak and vague convergence Glivenko-Cantelli theorem and Bernstein-Kantorovich invariance principle Stability of queueing systems.
Recovering measures from potential Statistical estimates obtained by the minimal distances method Some statistical tests based on N-distances Distances defined by zonoids N-distance tests of uniformity on the hypersphere. This book covers the method of metric distances and its application in probability theory and other fields. Inequalities; stochastic orderings Secondary: Distances between nested densities and a measure of the impact of the prior in Bayesian statistics.
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References [1] Azzalini, A. A class of distributions which includes the normal ones. You have access to this content.