Optimal model averaging by data perturbation for spatial noisy data-Reference-Cited by-同舟云学术

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Optimal model averaging by data perturbation for spatial noisy data

Published:2017-07-10 Issue:3 Volume:24 Page:415-431
ISSN:1352-8505
Container-title:Environmental and Ecological Statistics
language:en
Short-container-title:Environ Ecol Stat

Author:

Liao Jun,Zou Guohua,Gao Yan

Funder

Ministry of Science and Technology of the People’s Republic of China (CN)

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Statistics, Probability and Uncertainty,General Environmental Science,Statistics and Probability

Link

http://link.springer.com/article/10.1007/s10651-017-0377-z/fulltext.html

Reference25 articles.

1. Chang CH, Huang HC, Ing CK (2014) Asymptotic theory of generalized information criterion for geostatistical regression model selection. Ann Stat 42:2441–2468

2. Chen CS, Huang HC (2012) Geostatistical model averaging based on conditional information criteria. Environ Ecol Stat 19:23–35

3. Cressie N, Lahiri SN (1996) Asymptotics for REML estimation of spatial corvariance parameters. J Stat Plan Inference 50:327–341

4. Gao Y, Zhang X, Wang S, Zou G (2016) Model averaging based on leave-subject-out cross-validation. J Econom 192:139–151

5. Hansen BE (2007) Least squares model averaging. Econometrica 75:1175–1189

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