A New Copula-Based Approach for Counting: The Distorted and the Limiting Case

Enrico Bernardi () and Silvia Romagnoli ()
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Enrico Bernardi: University of Bologna, Department of Statistical Sciences “Paolo Fortunati”
Silvia Romagnoli: University of Bologna, Department of Statistical Sciences “Paolo Fortunati”

Chapter Chapter 5 in Counting Statistics for Dependent Random Events, 2021, pp 107-164 from Springer

Abstract: Abstract The purpose of this chapter is to examine in depth the new algorithm for counting with dependence, assuming at first to have a hierarchy in the dependence structure and then approaching the problem in very high dimensional cases. The hierarchical structure leads to a set of distorted distributions, selected by a random matrix representing the arrival policy of the random event, while for the tractability of high dimensional problems, one needs to work under approximation assumptions, resulting into a limiting copula-based counting approach.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-64250-1_5

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DOI: 10.1007/978-3-030-64250-1_5

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