Time forecasting model algorithms for detecting trends in monotonic data
This topic lists and describes time forecasting model algorithms that are suitable for detecting trends in monotonic data:
Linear
An example of a time forecasting model using the Linear algorithm
Robust Linear
An example of a time forecasting model using the Robust Linear algorithm
Robust Linear - Last Ramp
An example of a time forecasting model using the Robust Linear - Last Ramp algorithm
Robust Linear - Smoothed Last Ramp
An example of a time forecasting model using the Robust Linear - Smoothed Last Ramp algorithm
Quadratic
An example of a time forecasting model using the Quadratic algorithm
Cubic
An example of a time forecasting model using the Cubic algorithm
Exponential - Multiplicative Trend
An example of a time forecasting model using the Exponential - Multiplicative Trend algorithm
Robust Exponential Damping
An example of a time forecasting model using the Robust Exponential Damping algorithm
Robust Exponential Damping - Last Ramp
An example of a time forecasting model using the Robust Exponential Damping - Last Ramp algorithm
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