Author:
Verbelen Roel,Gong Lan,Antonio Katrien,Badescu Andrei,Lin Sheldon
Abstract
AbstractWe discuss how to fit mixtures of Erlangs to censored and truncated data by iteratively using the EM algorithm. Mixtures of Erlangs form a very versatile, yet analytically tractable, class of distributions making them suitable for loss modeling purposes. The effectiveness of the proposed algorithm is demonstrated on simulated data as well as real data sets.
Publisher
Cambridge University Press (CUP)
Subject
Economics and Econometrics,Finance,Accounting
Cited by
59 articles.
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