Time series smoother for effect detection

In environmental epidemiology, it is often encountered that multiple time series data with a long-term trend, including seasonality, cannot be fully adjusted by the observed covariates. The long-term trend is difficult to separate from abnormal short-term signals of interest. This paper addresses ho...

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Veröffentlicht in:	PloS one 2018-04, Vol.13 (4), p.e0195360
Hauptverfasser:	You, Cheng, Lin, Dennis K J, Young, S Stanley
Format:	Artikel
Sprache:	eng
Schlagworte:	Air Pollution Computer Simulation Data Interpretation, Statistical Earth Sciences Ecological and Environmental Phenomena Ecology and Environmental Sciences Environmental aspects Environmental effects Epidemiologic Methods Epidemiology Factor Analysis, Statistical Factorial design Humans Los Angeles Medical climatology Mortality Normal distribution Outdoor air quality Ozone Parameters People and places Physical Sciences Prevalence studies (Epidemiology) Regression Analysis Research and Analysis Methods Seasonal variations Smoothing Studies Temperature Time and Motion Studies Time Factors Time series Trends Weather
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