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DOI:	10.1371/journal.pone.0162489
论文题名:	Ultrahigh Dimensional Variable Selection for Interpolation of Point Referenced Spatial Data: A Digital Soil Mapping Case Study
作者:	Benjamin R. Fitzpatrick; David W. Lamb; Kerrie Mengersen
刊名:	PLOS ONE
ISSN:	1932-6203
出版年:	2016
发表日期:	2016-9-7
卷:	11, 期:9
语种:	英语
英文关键词:	Polynomials ; Interpolation ; Carbon sequestration ; Algorithms ; Physical geography ; Agricultural soil science ; Machine learning ; Linear regression analysis
英文摘要:	Modern soil mapping is characterised by the need to interpolate point referenced (geostatistical) observations and the availability of large numbers of environmental characteristics for consideration as covariates to aid this interpolation. Modelling tasks of this nature also occur in other fields such as biogeography and environmental science. This analysis employs the Least Angle Regression (LAR) algorithm for fitting Least Absolute Shrinkage and Selection Operator (LASSO) penalized Multiple Linear Regressions models. This analysis demonstrates the efficiency of the LAR algorithm at selecting covariates to aid the interpolation of geostatistical soil carbon observations. Where an exhaustive search of the models that could be constructed from 800 potential covariate terms and 60 observations would be prohibitively demanding, LASSO variable selection is accomplished with trivial computational investment.
URL:	http://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0162489&type=printable
Citation statistics:
资源类型:	期刊论文
标识符:	http://119.78.100.158/handle/2HF3EXSE/23508
Appears in Collections:	过去全球变化的重建影响、适应和脆弱性科学计划与规划气候变化与战略全球变化的国际研究计划气候减缓与适应气候变化事实与影响

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journal.pone.0162489.PDF（1115KB）	期刊论文	作者接受稿	开放获取	CC BY-NC-SA	View Download

作者单位:

Mathematical Sciences School, Queensland University of Technology (QUT), Brisbane, QLD 4001, Australia;Cooperative Research Centre for Spatial Information (CRCSI), Carlton, VIC 3053, Australia;Institute for Future Environments, Queensland University of Technology (QUT), Brisbane, QLD 4001, Australia;Cooperative Research Centre for Spatial Information (CRCSI), Carlton, VIC 3053, Australia;Precision Agriculture Research Group, University of New England, Armidale, NSW 2351, Australia;Mathematical Sciences School, Queensland University of Technology (QUT), Brisbane, QLD 4001, Australia;Cooperative Research Centre for Spatial Information (CRCSI), Carlton, VIC 3053, Australia;Institute for Future Environments, Queensland University of Technology (QUT), Brisbane, QLD 4001, Australia;ARC Centre of Excellence for Mathematical and Statistical Frontiers, Queensland University of Technology (QUT), Brisbane, QLD 4001, Australia

Recommended Citation:

Benjamin R. Fitzpatrick,David W. Lamb,Kerrie Mengersen. Ultrahigh Dimensional Variable Selection for Interpolation of Point Referenced Spatial Data: A Digital Soil Mapping Case Study[J]. PLOS ONE,2016-01-01,11(9)

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