29 citations · 63 across the 5 of their papers we have counts for
6 papers
A comprehensive empirical power comparison of univariate goodness-of-fit tests for the Laplace distribution
Alain Desgagné, Pierre Lafaye de Micheaux, Frédéric Ouimet
In this paper we present the results from an empirical power comparison of 40 goodness-of-fit tests for the univariate Laplace distribution, carried out using Monte Carlo simulatio…
Efficient and Robust Estimation of Linear Regression with Normal Errors
Alain Desgagné
Linear regression with normally distributed errors - including particular cases such as ANOVA, Student's t-test or location-scale inference - is a widely used statistical procedure…
An automatic robust Bayesian approach to principal component regression
Philippe Gagnon, Mylène Bédard, Alain Desgagné
Principal component regression uses principal components as regressors. It is particularly useful in prediction settings with high-dimensional covariates. The existing literature t…
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…
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…
Robustness to outliers in location-scale parameter model using log-regularly varying distributions
Alain Desgagné
Estimating the location and scale parameters is common in statistics, using, for instance, the well-known sample mean and standard deviation. However, inference can be contaminated…