The Log-Lindley distribution as an alternative to the beta regression model with applications in insurance

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<title>Log-Lindley distribution as an alternative to the beta regression model with applications in insurance</title>
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<namePart>Gómez-Déniz, Emilio</namePart>
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<abstract displayLabel="Summary">In this paper a new probability density function with bounded domain is presented. The new distribution arises from the generalized Lindley distribution proposed by Zakerzadeh and Dolati (2010). This new distribution that depends on two parameters can be considered as an alternative to the classical beta distribution. It presents the advantage of not including any special function in its formulation. After studying its most important properties, some useful results regarding insurance and inventory management applications are obtained. In particular, in insurance, we suggest a special class of distorted premium principles based on this distribution and we compare it with the well-known power dual premium principle. Since the mean of the new distribution can be normalized to give a simple parameter, this new model is appropriate to be used as a regression model when the response is bounded, being therefore an alternative to the beta regression model recently proposed in the statistical literature.</abstract>
<note type="statement of responsibility">Emilio Gómez-Déniz, Miguel A. Sordo, Enrique Calderín-Ojeda</note>
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<title>Insurance : mathematics and economics</title>
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<publisher>Oxford : Elsevier, 1990-</publisher>
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<identifier type="issn">0167-6687</identifier>
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<text>13/01/2014 Volumen 54 Número 1 - enero 2014 </text>
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