» Congress Schedule
In one overview: The WSC Scientific & Special Programme.
This session is being proposed on behalf of the Young Statistician group associated with the International Society for Business and Industrial Statistics (y-BIS), in collaboration with the Statistical Society of Canada’s New Investigator Committee. The aim of the session is to showcase recent work by early-career researchers at Canadian institutions in the realms of business, finance, and actuarial science. The topics presented in this session are intentionally diverse, but share the common thread of developing methods for practical use in the aforementioned domains. These topics include changepoint detection methods, stochastic approximation for data with triangular dependence, and robust, heavy-tailed versions of generalized linear models. The session is intended to be 90 minutes in durations with three speakers and no discussants (i.e., 30 minutes per speaker for their talk plus Q&A).
This session is organized jointly by the Young Statistician group associated with the International Society for Business and Industrial Statistics (y-BIS), in collaboration with the Statistical Society of Canada’s New Investigator Committee. The theme of the session is to showcase recent work by early-career researchers at Canadian institutions in the realms of business, finance, and actuarial science. The topics presented in this session are intentionally diverse, but share the common thread of developing methods for practical use in the aforementioned domains. These topics include changepoint detection methods, stochastic approximation for data with triangular dependence, and robust, heavy-tailed versions of generalized linear models.
Organiser: Dr Nathaniel Stevens
Chair: Dr Nathaniel Stevens
Speaker: Félix Camirand Lemyre
Speaker: Anne MacKay
Speaker: Philippe Gagnon
For more details on registrations and submissions for the 64th ISI World Statistics Congress, please first login to your account. If you do not have an account then you can create one below:
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