29 citations · 73 across the 15 of their papers we have counts for
3 papers · 1 filter
A New Bayesian Approach to Robustness Against Outliers in Linear Regression
Philippe Gagnon, Alain Desgagné, Mylène Bédard
Linear regression is ubiquitous in statistical analysis. It is well understood that conflicting sources of information may contaminate the inference when the classical normality of…
Weak Convergence and Optimal Tuning of the Reversible Jump Algorithm
Philippe Gagnon, Mylène Bédard, Alain Desgagné
The reversible jump algorithm is a useful Markov chain Monte Carlo method introduced by Green (1995) that allows switches between subspaces of differing dimensionality, and therefo…
Bayesian Robustness to Outliers in Linear Regression and Ratio Estimation
Alain Desgagné, Philippe Gagnon
Whole robustness is a nice property to have for statistical models. It implies that the impact of outliers gradually vanishes as they approach plus or minus infinity. So far, the B…