Bayesian Data Analysis for Gaussian Process Tomography
نویسندگان
چکیده
منابع مشابه
Bayesian Analysis of Censored Spatial Data Based on a Non-Gaussian Model
Abstract: In this paper, we suggest using a skew Gaussian-log Gaussian model for the analysis of spatial censored data from a Bayesian point of view. This approach furnishes an extension of the skew log Gaussian model to accommodate to both skewness and heavy tails and also censored data. All of the characteristics mentioned are three pervasive features of spatial data. We utilize data augme...
متن کاملEvaluation and Application of the Gaussian-Log Gaussian Spatial Model for Robust Bayesian Prediction of Tehran Air Pollution Data
Air pollution is one of the major problems of Tehran metropolis. Regarding the fact that Tehran is surrounded by Alborz Mountains from three sides, the pollution due to the cars traffic and other polluting means causes the pollutants to be trapped in the city and have no exit without appropriate wind guff. Carbon monoxide (CO) is one of the most important sources of pollution in Tehran air. The...
متن کاملInverse Gaussian process models for degradation analysis: A Bayesian perspective
This paper conducts a Bayesian analysis of inverse Gaussian process models for degradation modeling and inference. Novel features of the Bayesian analysis are the natural manners for incorporating subjective information, pooling of random effects information among product population, and a straightforward way of coping with evolving data sets for on-line prediction. A general Bayesian framework...
متن کاملPAC-Bayesian Theorems for Gaussian Process Classification
We present distribution-free generalization error bounds which apply to a wide class of approximate Bayesian Gaussian process classification (GPC) techniques, powerful nonparametric learning methods similar to Support Vector machines. The bounds use the PACBayesian theorem [8] for which we provide a simplified proof, leading to new insights into its relation to traditional VC type union bound t...
متن کاملFast Bayesian Inference for Gaussian Process Models
In many engineering and science disciplines, deterministic computer models or codes are used to simulate complex physical processes. The computer code mathematically describes the relationship between several input variables and one or more output variables. Often the computer models in question can be computationally demanding. Thus, direct evaluation of the code for optimization or validation...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Fusion Energy
سال: 2018
ISSN: 0164-0313,1572-9591
DOI: 10.1007/s10894-018-0205-y