Time forecasting model algorithms for detecting monotonic trends in data

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

Related topics

Time-forecasting-model-algorithms-for-detecting-trends-in-seasonal-time-series

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

Defining-algorithm-options

Linear

An example of a time forecasting model using the Linear algorithm

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Robust Linear

An example of a time forecasting model using the Robust Linear algorithm

PR_RUN_4794_35-ROBUST-LINEAR.png

Robust Linear - Last Ramp

An example of a time forecasting model using the Robust Linear - Last Ramp algorithm

PR_RUN_4795_1-ROBUST LINEAR LAST RAMP.png

Robust Linear - Smoothed Last Ramp

An example of a time forecasting model using the Robust Linear - Smoothed Last Ramp algorithm

PR_RUN_4942_6-ROBUST-LINEAR-SMOOTHED-LAST-RAMP-2.png

Quadratic

An example of a time forecasting model using the Quadratic algorithm

PR_RUN_4801_25-QUADRATIC-5.png

Cubic

An example of a time forecasting model using the Cubic algorithm

PR_RUN_4802_21-CUBIC-3.png


Exponential - Multiplicative Trend

An example of a time forecasting model using the Exponential - Multiplicative Trend algorithm

PR_RUN_4823_8-EXPONENTIAL-3.png


Nonnegative percentile-shift linear trend 

An example of a time forecasting model using the Nonnegative percentile-shift linear trend algorithm

nonnegative-algo.png

 

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