Spatial Bayesian latent factor regression modeling of coordinate-based meta-analysis data

Spatial Bayesian latent factor regression modeling of coordinate-based meta-analysis data.

Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the article are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to (i) identify areas of consistent activation; and (ii) build a ...

Bayesian Prediction in Spatial Data Analysis

Bayesian latent factor regression for functional and longitudinal data.

In studies involving functional data, it is commonly of interest to model the impact of predictors on the distribution of the curves, allowing flexible effects on not only the mean curve but also the distribution about the mean. Characterizing the curve for each subject as a linear combination of a high-dimensional set of potential basis functions, we place a sparse latent factor regression mod...

Bayesian Analysis of Survival Data with Spatial Correlation

Often in practice the data on the mortality of a living unit correlation is due to the location of the observations in the study‎. ‎One of the most important issues in the analysis of survival data with spatial dependence‎, ‎is estimation of the parameters and prediction of the unknown values in known sites based on observations vector‎. ‎In this paper to analyze this type of survival‎, ‎Cox...

Process Modeling by Bayesian Latent Variable Regression

Process Modeling by Bayesian Latent Variable Regression Mohamed N. Nounou, Bhavik R. Bakshi Prem K. Goel, Xiaotong Shen Department of Chemical Engineering Department of Statistics The Ohio State University, Columbus, OH 43210, USA Abstract Large quantities of measured data are being routinely collected in a variety of industries and used for extracting linear models for tasks such as, process c...