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Maximum Entropy Approach to the Loss Data Aggregation Problem

https://doi.org/10.2139/ssrn.2721018
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12/12 checkable references clean · checked 2026-10-08

Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.

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The 12 checked references that resolve
resolves10.21314/jop.2007.020
LDA at work: Deutsche Bank's approach to quantifying operational risk
resolves10.1007/978-0-387-31256-9
Convex Analysis and Nonlinear Optimization
resolves10.21314/jor.2010.208
On the aggregation of risk
resolves10.21314/jop.2014.143
Disentangling frequency models
resolves10.1016/j.insmatheco.2015.07.003
Maxentropic approach to decompound aggregate risk losses
resolves10.2139/ssrn.2664214
Loss Data Analysis: Analysis of the Sample Dependence In Density Reconstruction by Maxentropic Methods
resolves10.1016/j.insmatheco.2015.03.001
Two maxentropic approaches to determine the probability density of compound risk losses
resolves10.4171/rmi/475
A geometry on the space of probabilities II. Projective spaces and exponential families
resolves10.21314/jop.2013.117
A comparison of numerical approaches to determine the severity of losses
resolves10.1103/physrev.106.620
Information Theory and Statistical Mechanics
resolves10.1002/0470051310
Operational Risk
resolves10.1109/icmse.2012.6414357
Maximum-entropy-based operational risk loss distribution estimation of commercial banks
The 3 references without a DOI — listed, not checked
no DOI — not checkedref1
no DOI — not checkedref12
no DOI — not checkedref15
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