1 citations · 1 across the 4 of their papers we have counts for
4 papers
Scalable Bayesian Spatiotemporal Tensor Modeling for Censored and Missing Areal Data
Jose A. Ordoñez, Tsung-I Lin, Victor H. Lachos +1
We propose a new Bayesian approach for spatiotemporal areal data with censored and missing observations, where the response is represented as a tensor indexed by spatial units and…
Heckman Selection Contaminated Normal Model
Heeju Lim, Jose Alejandro Ordonez, Victor H. Lachos +1
The Heckman selection model is one of the most well-renounced econometric models in the analysis of data with sample selection. This model is designed to rectify sample selection b…
Spatial Censored Regression Models in R: The CensSpatial package
Jose A. Ordonez, Christian E. Galarza, Victor H. Lachos
CensSpatial is an R package for analyzing spatial censored data through linear models. It offers a set of tools for simulating, estimating, making predictions, and performing local…
Objective Bayesian analysis for spatial Student-t regression models
Jose A. Ordoñez, Marcos O. Prates, Larissa A. Matos +1
The choice of the prior distribution is a key aspect of Bayesian analysis. For the spatial regression setting a subjective prior choice for the parameters may not be trivial, from…