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A new statistical method for detecting trend turning
by
Li, Jianping
, Zhou, Xin
, Sun, Cheng
, Zuo, Bin
in
Climate
/ Climate change
/ Climate effects
/ Climate science
/ Climate trends
/ Detection
/ Slopes
/ Statistical analysis
/ Statistical methods
/ Test methods
/ Time series
/ Trends
2019
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Do you wish to request the book?
A new statistical method for detecting trend turning
by
Li, Jianping
, Zhou, Xin
, Sun, Cheng
, Zuo, Bin
in
Climate
/ Climate change
/ Climate effects
/ Climate science
/ Climate trends
/ Detection
/ Slopes
/ Statistical analysis
/ Statistical methods
/ Test methods
/ Time series
/ Trends
2019
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Journal Article
A new statistical method for detecting trend turning
2019
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Overview
When long time series are analyzed, two nearby periods may show significantly different trends, which is known as trend turning. Trend turning is common in climate time series and crucial when climate change is investigated. However, the available detection methods for climate trend turnings are relatively few, especially for the methods which have the ability of detecting multiple trend turnings. In this article, we propose a new methodology named as the running slope difference (RSD) t test to detect multiple trend turnings. This method employs a t-distributed statistic of slope difference to test the sub-series trend difference of the time series, thereby identifying the turning points. We compare the RSD t test method with some other existing trend turning detection methods in an idealized time series case and several climate time series cases. The results indicate that the RSD t test method is an effective tool for detecting climate trend turnings.
Publisher
Springer Nature B.V
Subject
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