output
20022025
most citedInferring population history with DIYABC: a user-friendly approach to Approximate Bayesian Computation

688 citations

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14 papers · 1 filter

stat.ME2023

Quantile Super Learning for independent and online settings with application to solar power forecasting

Herbert Susmann, Antoine Chambaz

Estimating quantiles of an outcome conditional on covariates is of fundamental interest in statistics with broad application in probabilistic prediction and forecasting. We propose…

stat.ME2019137 cited

Approximate Bayesian computation with the Wasserstein distance

Espen Bernton, Pierre E. Jacob, Mathieu Gerber +1

A growing number of generative statistical models do not permit the numerical evaluation of their likelihood functions. Approximate Bayesian computation (ABC) has become a popular…

stat.ME20188 cited

Model Selection for Mixture Models - Perspectives and Strategies

Gilles Celeux, Sylvia Fruewirth-Schnatter, Christian P. Robert

Determining the number G of components in a finite mixture distribution is an important and difficult inference issue. This is a most important question, because statistical infere…

stat.ME20173 cited

Some discussions on the Read Paper "Beyond subjective and objective in statistics" by A. Gelman and C. Hennig

Gilles Celeux, Jack Jewson, Julie Josse +2

This note is a collection of several discussions of the paper "Beyond subjective and objective in statistics", read by A. Gelman and C. Hennig to the Royal Statistical Society on A…

stat.ME2017

A recursive point process model for infectious diseases

Frederic Schoenberg, Marc Hoffmann, Ryan Harrigan

We introduce a new type of point process model to describe the incidence of contagious diseases. The model is a variant of the Hawkes self-exciting process and exhibits similar clu…

stat.ME20161 cited

Some comments about A Bayesian criterion for singular models by M. Drton and M. Plummer

Christian P. Robert, Judith Rousseau

These are written comments about the Read Paper A Bayesian criterion for singular models by M. Drton and M. Plummer, read to the Royal Statistical Society on October 5, 2016. The d…