Data augmentation for a Bayesian spatial model involving censored observations

Data augmentation for a Bayesian spatial model involving censored observations

Spatial environmental data sometimes include below detection limit observations (i.e. censored values reported as less than a level of detection). Historically, the most common practice for analysis of such data has been to replace the censored observations with some function of the level of detection (LOD), like LOD/2. We show that estimates and standard errors found using this single substitu...

Bayesian Analysis of Censored Spatial Data Based on a Non-Gaussian Model

Abstract: In this paper, we suggest using a skew Gaussian-log Gaussian model for the analysis of spatial censored data from a Bayesian point of view. This approach furnishes an extension of the skew log Gaussian model to accommodate to both skewness and heavy tails and also censored data. All of the characteristics mentioned are three pervasive features of spatial data. We utilize data augme...

A Bayesian Semiparametri AFT Model for Interval Censored Data

Spatial Modeling of Censored Survival Data

An important issue in survival data analysis is the identification of risk factors. Some of these factors are identifiable and explainable by presence of some covariates in the Cox proportional hazard model, while the others are unidentifiable or even immeasurable. Spatial correlation of censored survival data is one of these sources that are rarely considered in the literatures. In this paper,...

Bayesian Analysis of Censored Spatial Data Based on a Non-gaussian Model

In this paper, we suggest using a skew Gaussian-log Gaussian model for the analysis of spatial censored data from a Bayesian point of view. This approach furnishes an extension of the skew log Gaussian model to accommodate to both skewness and heavy tails and also censored data. All of the characteristics mentioned are three pervasive features of spatial data. We utilize data augmentation metho...