globalchange  > 过去全球变化的重建
DOI: 10.1007/s13253-018-00345-z
WOS记录号: WOS:000466342100003
论文题名:
Multivariate Bioclimatic Indices Modelling: A Coregionalised Approach
作者: Barber, Xavier1; Conesa, David2; Lopez-Quilez, Antonio2; Morales, Javier1
通讯作者: Barber, Xavier
刊名: JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS
ISSN: 1085-7117
EISSN: 1537-2693
出版年: 2019
卷: 24, 期:2, 页码:225-244
语种: 英语
英文关键词: Bioclimatology ; Coregionalised models ; Multivariate Bayesian spatial models ; Spatial prediction ; Spatial bioclimatic probability distribution
WOS关键词: VEGETATION ; GEOSTATISTICS ; MAP
WOS学科分类: Biology ; Mathematical & Computational Biology ; Statistics & Probability
WOS研究方向: Life Sciences & Biomedicine - Other Topics ; Mathematical & Computational Biology ; Mathematics
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.


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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/139572
Appears in Collections:过去全球变化的重建

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作者单位: 1.Univ Miguel Hernandez Elche, Ctr Invest Operat, Elche, Spain
2.Univ Valencia, Dpt Estadist & Invest Operat, Valencia, Spain

Recommended Citation:
Barber, Xavier,Conesa, David,Lopez-Quilez, Antonio,et al. Multivariate Bioclimatic Indices Modelling: A Coregionalised Approach[J]. JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS,2019-01-01,24(2):225-244
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