EFFICIENT ESTIMATION OF ERLANG MIXTURES USING iSCAD PENALTY WITH INSURANCE APPLICATION

Author:

Yin Cuihong,Lin X. Sheldon

Abstract

AbstractThe Erlang mixture model has been widely used in modeling insurance losses due to its desirable distributional properties. In this paper, we consider the problem of efficient estimation of the Erlang mixture model. We present a new thresholding penalty function and a corresponding EM algorithm to estimate model parameters and to determine the order of the mixture. Using simulation studies and a real data application, we demonstrate the efficiency of the EM algorithm.

Publisher

Cambridge University Press (CUP)

Subject

Economics and Econometrics,Finance,Accounting

Reference30 articles.

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