We provide user friendly software for Bayesian analysis of functional data models using pkg{WinBUGS}~1.4. The excellent properties of Bayesian analysis in this context are due to: (1) dimensionality reduction, which leads to low dimensional projection bases; (2) mixed model representation of functional models, which provides a modular approach to model extension; and (3) orthogonality of the principal component bases, which contributes to excellent chain convergence and mixing properties. Our paper provides one more, essential, reason for using Bayesian analysis for functional models: the existence of software
This dissertation mainly presents a novel Bayesian method for sparse functional data. Specifically, ...
Penalized splines can be viewed as BLUPs in a mixed model framework, which allows the use of mixed m...
From simple NLMs to complex GLMMs, this book describes how to use the GUI for WinBUGS - BugsXLA - an...
We provide user friendly software for Bayesian analysis of Functional Data Models using WinBUGS 1.4....
We provide user friendly software for Bayesian analysis of functional data models using WinBUGS 1.4....
We provide a MATLAB toolbox, BFDA, that implements a Bayesian hierarchical model to smooth multiple ...
WinBUGS is a fully extensible modular framework for constructing and analysing Bayesian full probabi...
A hands-on introduction to the principles of Bayesian modeling using WinBUGS Bayesian Modeling Using...
WinBUGS is a program for Bayesian model fitting by Gibbs sampling. WinBUGS has limited facilities fo...
The absence of user-friendly software has long been a major obstacle to the routine application of B...
Markov chain Monte Carlo (MCMC) methods have become a ubiquitous tool in Bayesian analysis. This pap...
Penalized splines can be viewed as BLUPs in a mixed model framework, which allows the use of mixed m...
<p>Current frontiers in complex stochastic modeling of high-dimensional processes include major emph...
Penalized splines can be viewed as BLUPs in a mixed model framework, which allows the use of mixed m...
Penalized splines can be viewed as BLUPs in a mixed model framework, which allows the use of mixed m...
This dissertation mainly presents a novel Bayesian method for sparse functional data. Specifically, ...
Penalized splines can be viewed as BLUPs in a mixed model framework, which allows the use of mixed m...
From simple NLMs to complex GLMMs, this book describes how to use the GUI for WinBUGS - BugsXLA - an...
We provide user friendly software for Bayesian analysis of Functional Data Models using WinBUGS 1.4....
We provide user friendly software for Bayesian analysis of functional data models using WinBUGS 1.4....
We provide a MATLAB toolbox, BFDA, that implements a Bayesian hierarchical model to smooth multiple ...
WinBUGS is a fully extensible modular framework for constructing and analysing Bayesian full probabi...
A hands-on introduction to the principles of Bayesian modeling using WinBUGS Bayesian Modeling Using...
WinBUGS is a program for Bayesian model fitting by Gibbs sampling. WinBUGS has limited facilities fo...
The absence of user-friendly software has long been a major obstacle to the routine application of B...
Markov chain Monte Carlo (MCMC) methods have become a ubiquitous tool in Bayesian analysis. This pap...
Penalized splines can be viewed as BLUPs in a mixed model framework, which allows the use of mixed m...
<p>Current frontiers in complex stochastic modeling of high-dimensional processes include major emph...
Penalized splines can be viewed as BLUPs in a mixed model framework, which allows the use of mixed m...
Penalized splines can be viewed as BLUPs in a mixed model framework, which allows the use of mixed m...
This dissertation mainly presents a novel Bayesian method for sparse functional data. Specifically, ...
Penalized splines can be viewed as BLUPs in a mixed model framework, which allows the use of mixed m...
From simple NLMs to complex GLMMs, this book describes how to use the GUI for WinBUGS - BugsXLA - an...