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Time-series analysis of disease data

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Time-series analysis of disease data
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8
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CC Attribution 3.0 Germany:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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Production Year2022
Production PlaceWageningen

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Abstract
In this session, Timothee Dub (Finnish Institute for Health and Welfare, Finland) & Tom Hengl (OpenGeoHub, Netherlands) discussed the basics of Time Series Analysis, including with panel data. We looked into how to take into account seasonality, how to identify a trend and how to investigate the relationship between two-time series, with a focus on practical tips and R packages. By the end of this lecture, participants are able to analyze surveillance data, identify seasonality and investigate potential trends.
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