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2.2.3.4.2 Algorithm for Trend Analysis
- Linear model
- \[y_t=intercept + slope \times t\]
- Quadratic model
- \[y_t=intercept + B_1 \times t + B_2 \times t^2\]
- Exponential growth model
- \[y_t= B_0 \times B_1^t\]
- Logistic model
- \[y_t= \frac{1}{B_0+ B_1 \times B_2^t}\]
- Statistics
- Mean absolute percentage error: \(MAPE = \sum_{t=1}^{n}\frac{|(y_t - \hat{y}_t)/y_t|}{n}\)
- Mean absolute deviation : \(MAD = \sum_{t=1}^{n}\frac{|y_t - \hat{y}_t|}{n}\)
- Mean squared deviation : \(MSD = \sum_{t=1}^{n}\frac{|y_t - \hat{y}_t|^2}{n}\)