Journal of the Iranian Statistical Society
پژوهشنامه انجمن آمار ایران
JIRSS
Basic Sciences
http://jirss.irstat.ir
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1726-4057
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2021
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Some New Results on Policy Limit Allocations
62Exx: Distribution theory
62Exx: Distribution theory
Original Paper
Original Paper
<p>Suppose that a policyholder faces $n$ risks X<sub>1</sub>, ..., X<sub>n</sub> which are insured under the policy limit with the total limit of l. Usually, the policyholder is asked to protect each X<sub>i</sub> with an arbitrary limit of l<sub>i</sub> such that ∑<sup>n</sup><sub>i=1</sub>l<sub>i</sub>=l. If the risks are independent and identically distributed with log-concave cumulative distribution function, using the notions of majorization and stochastic orderings, we prove that the equal limits provide the maximum of the expected utility of the wealth of policyholder. If the risks with log-concave distribution functions are independent and ordered in the sense of the reversed hazard rate order, we show that the equal limits is the most favourable allocation among the worst allocations. We also prove that if the joint probability density function is arrangement increasing, then the best arranged allocation maximizes the utility expectation of policyholderchr('39')s wealth. We apply the main results to the case when the risks are distributed according to a log-normal distribution.</p>
Arrangement Increasing Function, Log-Normal Distribution, Majorization, Schur-Convex Function, Stochastic Orders, Utility Function.
183
196
http://jirss.irstat.ir/browse.php?a_code=A-11-369-32&slc_lang=other&sid=1
Sirous
Fathi Manesh
sirus_60@yahoo.com
`10031947532846004107`

10031947532846004107
Yes
Department of Statistics, University of Kurdistan, Sanandaj, Iran
Muhyiddin
Izadi
izadi_552@yahoo.com
`10031947532846004108`

10031947532846004108
No
Department of Statistics, Razi University, Kermanshah, Iran
Baha-Eldin
Khaledi
bkhaledi@fiu.edu
`10031947532846004109`

10031947532846004109
No
Department of Mathematics and Statistics, Florida International University, Miami, FL 33199, USA