Hierarchical models

Bayesian inference for finite populations under spatial process settings

We develop a Bayesian model–based approach to finite population estimation accounting for spatial dependence. Our innovation here is a framework that achieves inference for finite population quantities in spatial process settings. A key distinction …

Model-Based Combination of Spatial Information for Stream Networks

Evolutionary improvements in Geographic Information Systems (GIS) now routinely allow the management and mapping of spatial-temporal information. In response, the development of statistical models to combine information of different types and spatial …

Statistical Methods for Ecological Assessment Of Riverine Systems By Combining Information From Multiple Sources

The assessment of environmental risk and the evaluation of environmental policies increasingly require accurate and relevant information about the environment. For policy makers and stakeholders to evaluate possible policy changes, an understanding …