Scholarly Works - Book sections
Book section
·
January 1, 2021
Spatially-referenced multivariate data is becoming increasingly common. Here, we focus on data in the form of vectors observed at a finite set of spatial locations. Regression models are of interest in order to explain the response vectors as well as to pr ...
Full text
Cite
Book section
·
January 1, 2013
We propose a class of misaligned data models for addressing typical small area estimation (SAE) problems. In particular, we extend hierarchical Bayesian atom-based models for spatial misalignment to the SAE context enabling use of auxiliary covariates, whi ...
Full text
Cite
Book section
·
October 11, 2012
This chapter addresses the settings where there is need to specify knots in order to fit desired spatial models. That is, it seeks to fit hierarchical models in order to enable full inference and to adequately capture uncertainty. The chapter adopts an app ...
Full text
Cite
Book section
·
January 1, 2006
In the past 20 years, we have seen a remarkable rejuvenation of the Bayesian inference paradigm. Novel computational tools in conjunction with inexpensive high-speed computing have enabled the fitting of challenging Bayesian models. As a result, a more int ...
Full text
Cite
Book section
·
January 1, 2006
A recent article in Science magazine (286, 19 November 1999, pp. 1460–1464) noted the rejuvenation of the Bayesian inference paradigm and its increasingly warmer reception in the scientific community. Pertinent here, is its recent application to a wide ran ...
Full text
Cite
Book section
·
January 1, 2001
The vignette series concludes with 22 contributions in Theory and Methods. It is, of course, impossible to cover all of theory and methods with so few articles, but we hope that a snapshot of what was, and what may be, is achieved. This is the essence of “ ...
Cite
