globalchange  > 气候减缓与适应
DOI: 10.1175/JCLI-D-17-0334.1
Scopus记录号: 2-s2.0-85047074938
论文题名:
Memory matters: A case for granger causality in climate variability studies
作者: McGraw M.C.; Barnes E.A.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2018
卷: 31, 期:8
起始页码: 3289
结束页码: 3300
语种: 英语
英文关键词: Regression analysis ; Statistical techniques ; Statistics
Scopus关键词: Climatology ; Linear regression ; Regression analysis ; Statistics ; Autocorrelated ; Causal relationships ; Climate variability ; Granger Causality ; Granger causality analysis ; Statistical techniques ; Statistical tests ; climate variation ; data set ; Granger causality test ; information ; Monte Carlo analysis ; regression analysis
英文摘要: In climate variability studies, lagged linear regression is frequently used to infer causality. While lagged linear regression analysis can often provide valuable information about causal relationships, lagged regression is also susceptible to overreporting significant relationships when one or more of the variables has substantial memory (autocorrelation). Granger causality analysis takes into account the memory of the data and is therefore not susceptible to this issue. A simple Monte Carlo example highlights the advantages of Granger causality, compared to traditional lagged linear regression analysis in situations with one or more highly autocorrelated variables. Differences between the two approaches are further explored in two illustrative examples applicable to large-scale climate variability studies. Given that Granger causality is straightforward to calculate, Granger causality analysis may be preferable to traditional lagged regression analysis when one or more datasets has large memory. © 2018 American Meteorological Society.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/111609
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作者单位: Department of Atmospheric Science, Colorado State University, Fort Collins, CO, United States

Recommended Citation:
McGraw M.C.,Barnes E.A.. Memory matters: A case for granger causality in climate variability studies[J]. Journal of Climate,2018-01-01,31(8)
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