LRMoE-package: LRMoE: Logit-Weighted Reduced Mixture-of-Experts
In UofTActuarial/LRMoE: Logit-Weighted Reduced Mixture-of-Experts
Description
The Logit-Weighted Reduced Mixture-of-Experts (LRMoE)
proposed by Fung et al. (2019) is a flexible framework actuarial loss modelling.
For more details, see Fung et al. (2019) "A class of mixture of experts models for general insurance: Theoretical developments"
published in Insurance: Mathematics and Economics, and
Fung et al. (2019) "A CLASS OF MIXTURE OF EXPERTS MODELS FOR GENERAL INSURANCE: APPLICATION TO CORRELATED CLAIM FREQUENCIES"
in ASTIN Bulletin: The Journal of the IAA.
Author(s)
Maintainer: Spark Tseung spark.tseung@mail.utoronto.ca
Authors:
Tsz Chai Fung
Andrei L. Badescu
Sheldon X. Lin
Siyi Wei
UofTActuarial/LRMoE documentation built on Feb. 18, 2022, 1:36 a.m.
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Description
The Logit-Weighted Reduced Mixture-of-Experts (LRMoE) proposed by Fung et al. (2019) is a flexible framework actuarial loss modelling. For more details, see Fung et al. (2019) "A class of mixture of experts models for general insurance: Theoretical developments" published in Insurance: Mathematics and Economics, and Fung et al. (2019) "A CLASS OF MIXTURE OF EXPERTS MODELS FOR GENERAL INSURANCE: APPLICATION TO CORRELATED CLAIM FREQUENCIES" in ASTIN Bulletin: The Journal of the IAA.
Author(s)
Maintainer: Spark Tseung spark.tseung@mail.utoronto.ca
Authors:
Tsz Chai Fung
Andrei L. Badescu
Sheldon X. Lin
Siyi Wei
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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