hernández, damián g. samengo, inés

is well sampled. The other variable, as well as the joint and conditional distributions, can be severely undersampled. We obtain a consistent estimator that presents very low bias, outperforming previous methods even when the sampled data contain few coincidences. As with other Bayesian estimators, our proposal focuses on the strength of the intera...

hernández, damián g. samengo, inés

is well sampled. The other variable, as well as the joint and conditional distributions, can be severely undersampled. We obtain a consistent estimator that presents very low bias, outperforming previous methods even when the sampled data contain few coincidences. As with other Bayesian estimators, our proposal focuses on the strength of the intera...

Chevallier, Juliette Debavelaere, Vianney Allassonnière, Stéphanie

This paper provides a coherent framework for studying longitudinal manifold-valued data. We introduce a Bayesian mixed-effects model which allows to estimate both a group-representative piecewise-geodesic trajectory in the Riemannian space of shape and inter-individual variability. We prove the existence of the maximum a posteriori estimate and its...

Rebei, Nooman SBIA, RASHID

This paper documents the determinants of real oil price in the global market based on SVAR model embedding transitory and permanent shocks on oil demand and supply as well as speculative disturbances. We find evidence of significant differences in the propagation mechanisms of transitory versus permanent shocks, pointing to the importance of disent...

Chevallier, Juliette Debavelaere, Vianney Allassonnière, Stéphanie

This paper provides a coherent framework for studying longitudinal manifold-valued data. We introduce a Bayesian mixed-effects model which allows to estimate both a group-representative piecewise-geodesic trajectory in the Riemannian space of shape and inter-individual variability. We prove the existence of the maximum a posteriori estimate and its...

Galharret, Jean-Michel Philippe, Anne

In human sciences, mediation designates a particular causal phenomenon where the effect of a variable X on another variable Y passes (par-tially or entirely) through a third variable M. The parameters of interest in mediation models are the direct effect of X on Y and the indirect effect of X on Y through M. We use a Bayesian framework to estimate ...

Galharret, Jean-Michel Philippe, Anne

In human sciences, mediation designates a particular causal phenomenon where the effect of a variable X on another variable Y passes (par-tially or entirely) through a third variable M. The parameters of interest in mediation models are the direct effect of X on Y and the indirect effect of X on Y through M. We use a Bayesian framework to estimate ...

Galharret, Jean-Michel Philippe, Anne

In human sciences, mediation designates a particular causal phenomenon where the effect of a variable X on another variable Y passes (par-tially or entirely) through a third variable M. The parameters of interest in mediation models are the direct effect of X on Y and the indirect effect of X on Y through M. We use a Bayesian framework to estimate ...

Galharret, Jean-Michel Philippe, Anne

In human sciences, mediation designates a particular causal phenomenon where the effect of a variable X on another variable Y passes (par-tially or entirely) through a third variable M. The parameters of interest in mediation models are the direct effect of X on Y and the indirect effect of X on Y through M. We use a Bayesian framework to estimate ...

Galharret, Jean-Michel Philippe, Anne

In human sciences, mediation designates a particular causal phenomenon where the effect of a variable X on another variable Y passes (par-tially or entirely) through a third variable M. The parameters of interest in mediation models are the direct effect of X on Y and the indirect effect of X on Y through M. We use a Bayesian framework to estimate ...