9 citations · 10 across the 7 of their papers we have counts for
7 papers
Tree Pólya Splitting distributions for multivariate count data
Samuel Valiquette, Jean Peyhardi, Éric Marchand +2
In this article, we develop a new class of multivariate distributions adapted for count data, called Tree Pólya Splitting. This class results from the combination of a univariate d…
Asymptotic tail properties of Poisson mixture distributions
Samuel Valiquette, Gwladys Toulemonde, Jean Peyhardi +2
Count data are omnipresent in many applied fields, often with overdispersion. With mixtures of Poisson distributions representing an elegant and appealing modelling strategy, we fo…
Choice of mixture Poisson models based on Extreme value theory
Samuel Valiquette, Frédéric Mortier, Jean Peyhardi +1
Count data are omnipresent in many applied fields, often with overdispersion due to an excess of zeroes or extreme values. With mixtures of Poisson distributions representing an el…
Splitting models for multivariate count data
Pierre Fernique, Jean Peyhardi, Jean-Baptiste Durand
Considering discrete models, the univariate framework has been studied in depth compared to the multivariate one. This paper first proposes two criteria to define a sensu stricto m…
Item response models for the longitudinal analysis of health-related quality of life in cancer clinical trials
Antoine Barbieri, Jean Peyhardi, Thierry Conroy +3
Statistical research regarding health-related quality of life (HRQoL) is a major challenge to better evaluate the impact of the treatments on their everyday life and to improve pat…
Partitioned conditional generalized linear models for categorical data
Jean Peyhardi, Catherine Trottier, Yann Guédon
In categorical data analysis, several regression models have been proposed for hierarchically-structured response variables, e.g. the nested logit model. But they have been formall…
A new specification of generalized linear models for categorical data
Jean Peyhardi, Catherine Trottier, Yann Guédon
Regression models for categorical data are specified in heterogeneous ways. We propose to unify the specification of such models. This allows us to define the family of reference m…