Efficient estimation of Erlang mixtures using iSCAD penalty with insurance application

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      <subfield code="a">Efficient estimation of Erlang mixtures using iSCAD penalty with insurance application</subfield>
      <subfield code="c">Cuihong Yin and X. Sheldon Lin</subfield>
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      <subfield code="a">The 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.</subfield>
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      <subfield code="d">Belgium : ASTIN and AFIR Sections of the International Actuarial Association</subfield>
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      <subfield code="g">01/09/2016 Volumen 46 Número 3 - septiembre 2016 , p. 780-799</subfield>
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