Zobrazeno 1 - 10
of 54
pro vyhledávání: '"Hélène Cossette"'
Publikováno v:
Risks, Vol 9, Iss 1, p 4 (2020)
In the past 25 years, computer scientists and statisticians developed machine learning algorithms capable of modeling highly nonlinear transformations and interactions of input features. While actuaries use GLMs frequently in practice, only in the pa
Externí odkaz:
https://doaj.org/article/a71b429fdf5b463fb8cd9061188c609a
Publikováno v:
Insurance: Mathematics and Economics. 111:102-120
We offer a new perspective on risk aggregation with FGM copulas. Along the way, we discover new results and revisit existing ones, providing simpler formulas than one can find in the existing literature. This paper builds on two novel representations
Publikováno v:
Applied Stochastic Models in Business and Industry.
Autor:
Jimmy Li, Hélène Cossette-Roberge, Dènahin Hinnoutondji Toffa, Charles Deacon, Mark Robert Keezer
Publikováno v:
Epilepsy Research. 193:107159
Publikováno v:
Applied Stochastic Models in Business and Industry. 37:675-702
Publikováno v:
RNA Biology
article-version (VoR) Version of Record
article-version (VoR) Version of Record
RNAs are highly regulated at the post-transcriptional level in neurodegenerative diseases and just a few mutations can significantly affect the fate of neuronal cells. To date, the impact of G-quadruplex (G4) regulation in neurodegenerative diseases
Publikováno v:
Insurance: Mathematics and Economics. 93:246-261
For an insurance company, effective risk management requires an appropriate measurement of the risk associated with an insurance portfolio. The objective of the present paper is to study properties of ruin-based risk measures defined within discrete-
Publikováno v:
Insurance: Mathematics and Economics. 92:47-60
In risk management, capital requirements are most often based on risk measurements of the aggregation of individual risks treated as random variables. The dependence structure between such random variables has a strong impact on the behavior of the a
Publikováno v:
Risks, Vol 9, Iss 4, p 4 (2021)
In the past 25 years, computer scientists and statisticians developed machine learning algorithms capable of modeling highly nonlinear transformations and interactions of input features. While actuaries use GLMs frequently in practice, only in the pa
Publikováno v:
Computational Statistics & Data Analysis. 173:107506