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pro vyhledávání: '"Gagnon, Philippe"'
Autor:
Gagnon, Philippe, Desgagné, Alain
Heavy-tailed models are often used as a way to gain robustness against outliers in Bayesian analyses. On the other side, in frequentist analyses, M-estimators are often employed. In this paper, the two approaches are reconciled by considering M-estim
Externí odkaz:
http://arxiv.org/abs/2408.10478
Autor:
Gagnon, Philippe, Maire, Florian
Lifted samplers form a class of Markov chain Monte Carlo methods which has drawn a lot attention in recent years due to superior performance in challenging Bayesian applications. A canonical example of such sampler is the one that is derived from a r
Externí odkaz:
http://arxiv.org/abs/2405.15952
Autor:
Gagnon, Philippe, Wang, Yuxi
Publikováno v:
Computational Statistics & Data Analysis, 194, 1-16 (2024)
Generalized linear models (GLMs) form one of the most popular classes of models in statistics. The gamma variant is used, for instance, in actuarial science for the modelling of claim amounts in insurance. A flaw of GLMs is that they are not robust a
Externí odkaz:
http://arxiv.org/abs/2305.13462
Publikováno v:
Journal of Machine Learning Research, 24(248), 1-59 (2023)
Multiple-try Metropolis (MTM) is a popular Markov chain Monte Carlo method with the appealing feature of being amenable to parallel computing. At each iteration, it samples several candidates for the next state of the Markov chain and randomly select
Externí odkaz:
http://arxiv.org/abs/2211.11613
Autor:
Gagnon, Philippe, Hayashi, Yoshiko
Publikováno v:
Statistics & Probability Letters, 193, 1-8 (2023)
Bayesian Student-$t$ linear regression is a common robust alternative to the normal model, but its theoretical properties are not well understood. We aim to fill some gaps by providing analyses in two different asymptotic scenarios. The results allow
Externí odkaz:
http://arxiv.org/abs/2204.02299
Autor:
Gagnon, Philippe
Publikováno v:
Bayesian Analysis 18(3): 841-864 (September 2023)
Including prior information about model parameters is a fundamental step of any Bayesian statistical analysis. It is viewed positively by some as it allows, among others, to quantitatively incorporate expert opinion about model parameters. It is view
Externí odkaz:
http://arxiv.org/abs/2110.09556
Autor:
Gagnon, Philippe, Wang, Yuxi
Publikováno v:
In Computational Statistics and Data Analysis June 2024 194
Autor:
Schmon, Sebastian M, Gagnon, Philippe
High-dimensional limit theorems have been shown useful to derive tuning rules for finding the optimal scaling in random-walk Metropolis algorithms. The assumptions under which weak convergence results are proved are however restrictive: the target de
Externí odkaz:
http://arxiv.org/abs/2104.06384
Autor:
Gagnon, Philippe, Maire, Florian
Publikováno v:
Bernoulli 30(3), 2301-2325, (August 2024)
A Peskun ordering between two samplers, implying a dominance of one over the other, is known among the Markov chain Monte Carlo community for being a remarkably strong result. It is however also known for being a result that is notably difficult to e
Externí odkaz:
http://arxiv.org/abs/2003.05492