Supplemental material
Open access
1,317
Views
3
CrossRef citations to date
0
Altmetric
Spatiotemporal Modeling
Dynamically Updated Spatially Varying Parameterizations of Hierarchical Bayesian Models for Spatial Data
Mark R. BassBarclays Services Limited, London, UK
& Sujit K. SahuUniversity of Southampton, Southampton, UK
Pages 105-116
|
Received 01 Jun 2016, Published online: 19 Sep 2018
Related Research Data
Dynamically Updated Spatially Varying Parameterizations of Hierarchical Bayesian Models for Spatial Data
Source:
figshare Academic Research System
Matrix Algebra From a Statistician’s Perspective
Source:
Springer New York
Monte Carlo Statistical Methods
Source:
Springer New York
Spatial Variation
Source:
Springer New York
A Bayesian approach to hedonic price analysis
Source:
Wiley-Blackwell
Dynamically Updated Spatially Varying Parameterizations of Hierarchical Bayesian Models for Spatial Data
Source:
Taylor & Francis
A Spatio-Temporal Downscaler for Output From Numerical Models
Source:
Springer Nature
Inconsistent Estimation and Asymptotically Equal Interpolations in Model-Based Geostatistics
Source:
Informa UK Limited
Fixed Rank Kriging
Source:
Wiley
A comparison of centring parameterisations of Gaussian process-based models for Bayesian computation using MCMC
Source:
Springer Nature
Air quality modelling using the Met Office Unified Model (AQUM OS24-26): model description and initial evaluation
Source:
Copernicus Publications
Probabilistic forecasts, calibration and sharpness
Source:
Wiley
High-Resolution Space–Time Ozone Modeling for Assessing Trends
Source:
Informa UK Limited
Efficient parametrisations for normal linear mixed models
Source:
Oxford University Press (OUP)
spTimer: Spatio-Temporal Bayesian Modeling Using R
Source:
Foundation for Open Access Statistics
ggplot2
Source:
Springer New York
A spatially varying coefficient model for mapping PM10 air quality at the European scale
Source:
Elsevier BV
Dynamically Updated Spatially Varying Parameterizations of Hierarchical Bayesian Models for Spatial Data
Source:
Taylor & Francis
To Center or Not to Center: That Is Not the Question—An Ancillarity–Sufficiency Interweaving Strategy (ASIS) for Boosting MCMC Efficiency
Source:
Informa UK Limited
A Bayesian analysis of kriging
Source:
Informa UK Limited
Sampling-Based Approaches to Calculating Marginal Densities
Source:
Informa UK Limited
A Bayesian analysis of kriging
Source:
Informa UK Limited
Spatial Modeling With Spatially Varying Coefficient Processes
Source:
Informa UK Limited
Sampling-Based Approaches to Calculating Marginal Densities
Source:
Informa UK Limited
spBayesfor Large Univariate and Multivariate Point-Referenced Spatio-Temporal Data Models
Source:
Foundation for Open Access Statistic
A spatiotemporal model for Mexico City ozone levels
Source:
Wiley
Inference from Iterative Simulation Using Multiple Sequences
Source:
The Institute of Mathematical Statistics
Related research
People also read lists articles that other readers of this article have read.
Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.
Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.