Bayesian spatially varying coefficient models in the spBayes R package
Bayesian spatially varying coefficient models in the spBayes R package
复制标题
spBayes R 包中的贝叶斯空间变化系数模型
DOI:
10.1016/j.envsoft.2019.104608
复制
发表时间:
2020
影响因子:
4.9
通讯作者:
Banerjee, Sudipto
中科院分区:
文献类型:
--
作者:
Finley, Andrew O.;Banerjee, Sudipto
This paper describes and illustrates new functionality for fitting spatially varying coefficients models in thespBayes(version 0.4–2) R package. The newspSVCfunction uses a computationally efficient Markov chain Monte Carlo algorithm and extends currentspBayesfunctions, that fit only space-varying intercept regression models, to fit independent or multivariate Gaussian process random effects for any set of columns in the regression design matrix. Newly added OpenMP parallelization options forspSVCare discussed and illustrated, as well as helper functions for joint and point-wise prediction and model fit diagnostics. The utility of the proposed models is illustrated using a PM10analysis over central Europe.
DOI:
10.1214/16-aoas931
发表时间:
2016-09
期刊:
The annals of applied statistics
影响因子:
--
作者:
Datta A;Banerjee S;Finley AO;Hamm NAS;Schaap M
通讯作者:
Schaap M
影响因子:
5.8
作者:
Carpenter, Bob;Gelman, Andrew;Riddell, Allen
通讯作者:
Riddell, Allen
DOI:
10.1111/rssc.12103
发表时间:
2015
期刊:
Journal of the Royal Statistical Society: Series C (Applied Statistics)
影响因子:
--
作者:
K. Bakar;P. Kokic;Huidong Jin
通讯作者:
Huidong Jin