research
∙
08/03/2023
The use of the EM algorithm for regularization problems in high-dimensional linear mixed-effects models
The EM algorithm is a popular tool for maximum likelihood estimation but...
share
research
∙
10/11/2021
Spatial Censored Regression Models in R: The CensSpatial package
CensSpatial is an R package for analyzing spatial censored data through ...
research
∙
09/28/2020
On moments of folded and doubly truncated multivariate extended skew-normal distributions
This paper develops recurrence relations for integrals that relate the d...
research
∙
09/22/2020
Finite mixture modeling of censored and missing data using the multivariate skew-normal distribution
Finite mixture models have been widely used to model and analyze data fr...
research
∙
07/29/2020
Approximate inferences for nonlinear mixed effects models with scale mixtures of skew-normal distributions
Nonlinear mixed effects models have received a great deal of attention i...
research
∙
07/29/2020
Moments of the doubly truncated selection elliptical distributions with emphasis on the unified multivariate skew-t distribution
In this paper, we compute doubly truncated moments for the selection ell...
research
∙
07/02/2020
A robust nonlinear mixed-effects model for COVID-19 deaths data
The analysis of complex longitudinal data such as COVID-19 deaths is cha...
research
∙
04/09/2020
Objective Bayesian analysis for spatial Student-t regression models
The choice of the prior distribution is a key aspect of Bayesian analysi...
research
∙
02/03/2020
Scale mixture of skew-normal linear mixed models with within-subject serial dependence
In longitudinal studies, repeated measures are collected over time and h...
research
∙
05/19/2018
