Hierarchical Bayesian fatigue data analysis

Analysis of Hierarchical Bayesian Models for Large Space Time Data of the Housing Prices in Tehran

Housing price data is correlated to their location in different neighborhoods and their correlation is type of spatial (location). The price of housing is varius in different months, so they also have a time correlation. Spatio-temporal models are used to analyze this type of the data. An important purpose of reviewing this type of the data is to fit a suitable model for the spatial-temporal an...

Bayesian Prediction in Spatial Data Analysis

Learning Hierarchical Bayesian Networks for Large-Scale Data Analysis

Bayesian network learning is a useful tool for exploratory data analysis. However, applying Bayesian networks to the analysis of large-scale data, consisting of thousands of attributes, is not straightforward because of the heavy computational burden in learning and visualization. In this paper, we propose a novel method for large-scale data analysis based on hierarchical compression of informa...

Bayesian hierarchical multi-subject multiscale analysis of functional MRI data

We develop a methodology for Bayesian hierarchical multi-subject multiscale analysis of functional Magnetic Resonance Imaging (fMRI) data. We begin by modeling the brain images temporally with a standard general linear model. After that, we transform the resulting estimated standardized regression coefficient maps through a discrete wavelet transformation to obtain a sparse representation in th...

Best Bases Bayesian Hierarchical Classifier for Hyperspectral Data Analysis

Classification of hyperspectral data is challenging because of high dimensionality inputs coupled with possible high dimensional outputs and scarcity of labeled information. Previously, a multiclassifier system was formulated in a binary hierarchical framework to group classes for accurate, rapid discrimination. In order to improve performance for small sample sizes, a new approach was develope...