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DOI | 10.1007/s13253-018-00345-z |
Multivariate Bioclimatic Indices Modelling: A Coregionalised Approach | |
Barber, Xavier1; Conesa, David2; Lopez-Quilez, Antonio2; Morales, Javier1 | |
发表日期 | 2019 |
ISSN | 1085-7117 |
EISSN | 1537-2693 |
卷号 | 24期号:2页码:225-244 |
英文摘要 | A methodological approach for modelling the spatial multivariate distribution of multiple bioclimatic indices is presented. The value of the indices is modelled by means of a Bayesian conditional coregionalised linear model. Elicitation of prior distributions and approximation of posterior distributions of the parameters in the proposed model are also discussed. A posterior predictive distribution and a spatial bioclimatic probability distribution for each bioclimatic index are obtained. This allows researchers to obtain the probability of each location belonging to different bioclimates. The presented methodology is applied in a practical setting showing that the spatial bioclimatic probability distributions are more realistic than the ones obtained in the univariate setting, while providing an interesting tool in the context of climate change. |
WOS研究方向 | Life Sciences & Biomedicine - Other Topics ; Mathematical & Computational Biology ; Mathematics |
来源期刊 | JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS
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文献类型 | 期刊论文 |
条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/98601 |
作者单位 | 1.Univ Miguel Hernandez Elche, Ctr Invest Operat, Elche, Spain; 2.Univ Valencia, Dpt Estadist & Invest Operat, Valencia, Spain |
推荐引用方式 GB/T 7714 | Barber, Xavier,Conesa, David,Lopez-Quilez, Antonio,et al. Multivariate Bioclimatic Indices Modelling: A Coregionalised Approach[J],2019,24(2):225-244. |
APA | Barber, Xavier,Conesa, David,Lopez-Quilez, Antonio,&Morales, Javier.(2019).Multivariate Bioclimatic Indices Modelling: A Coregionalised Approach.JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS,24(2),225-244. |
MLA | Barber, Xavier,et al."Multivariate Bioclimatic Indices Modelling: A Coregionalised Approach".JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS 24.2(2019):225-244. |
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