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Inference of trends in time series
Author(s) -
Wu Wei Biao,
Zhao Zhibiao
Publication year - 2007
Publication title -
journal of the royal statistical society: series b (statistical methodology)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.523
H-Index - 137
eISSN - 1467-9868
pISSN - 1369-7412
DOI - 10.1111/j.1467-9868.2007.00594.x
Subject(s) - inference , series (stratigraphy) , statistic , econometrics , confidence and prediction bands , statistical inference , test statistic , construct (python library) , time series , statistics , confidence interval , mathematics , statistical hypothesis testing , computer science , artificial intelligence , geology , paleontology , programming language
Summary. We consider statistical inference of trends in mean non‐stationary models. A test statistic is proposed for the existence of structural breaks in trends. On the basis of a strong invariance principle of stationary processes, we construct simultaneous confidence bands with asymptotically correct nominal coverage probabilities. The results are applied to global warming temperature data and Nile river flow data. Our confidence band of the trend of the global warming temperature series supports the claim that the trend is increasing over the last 150 years.