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pro vyhledávání: '"Trufin, Julien"'
Autor:
Denuit, Michel, Trufin, Julien
Publikováno v:
In Insurance Mathematics and Economics September 2024 118:123-128
Publikováno v:
In Insurance Mathematics and Economics July 2024 117:130-139
Boosting techniques and neural networks are particularly effective machine learning methods for insurance pricing. Often in practice, there are nevertheless endless debates about the choice of the right loss function to be used to train the machine l
Externí odkaz:
http://arxiv.org/abs/2103.03635
Autor:
Sinner, Corinne, Dominicy, Yves, Trufin, Julien, Waterschoot, Wout, Weber, Patrick, Ley, Christophe
Power laws and power laws with exponential cut-off are two distinct families of distributions on the positive real half-line. In the present paper, we propose a unified treatment of both families by building a family of distributions that interpolate
Externí odkaz:
http://arxiv.org/abs/2012.13348
Autor:
Mesfioui Mhamed, Trufin Julien
Publikováno v:
Dependence Modeling, Vol 9, Iss 1, Pp 385-393 (2021)
In this paper, we investigate sufficient conditions for preservation property of the dispersive order for the smallest and largest order statistics of homogeneous dependent random vectors. Moreover, we establish sufficient conditions for ordering wit
Externí odkaz:
https://doaj.org/article/e9320ce023834f9e8002d49c088913c0
Akademický článek
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Publikováno v:
In Insurance Mathematics and Economics November 2021 101 Part B:163-172
We introduce a new five-parameter family of size distributions on the semi-finite interval $[x_0, \infty), x_0 \geqslant 0$, with two attractive features. First, it interpolates between power laws, such as the Pareto distribution, and power laws with
Externí odkaz:
http://arxiv.org/abs/1606.04430
Publikováno v:
In Insurance Mathematics and Economics July 2020 93:246-261
Publikováno v:
In Insurance Mathematics and Economics March 2020 91:202-208