Time forecasting model algorithms for detecting trends in seasonal time series

This topic lists and describes time forecasting model algorithms that are suitable for detecting trends in monotonic data:

Linear - By Time Shifts

An example of a time forecasting model using the Linear - By Time Shifts algorithm

PR_RUN_4821_21-BY-TIME-SHIFTS-2.png

Holt-Winters

An example of a time forecasting model using the Holt-Winters algorithm

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Linear - Yearly Time Shift

An example of a time forecasting model using the Linear - Yearly Time Shift algorithm

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Related topics

Time-forecasting-model-algorithms-for-detecting-monotonic-trends-in-data

Time-forecasting-model-algorithms-for-detecting-trends-and-seasonal-components-in-data

 

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