Working on All Categories · ARIMA(1, 0, 1).
Change it on the Demand Analysis page.
ARIMA Order Specification
ARIMA Model Formula
$$\Delta Y_t = c + \phi_1 \Delta Y_{t-1} + \varepsilon_t + \theta_1 \varepsilon_{t-1}$$
Historical Demand vs 6-Month ARIMA Forecast
6-Month Forecast Values
| Month | Forecast ($\hat{Y}$) | Lower 95% CI | Upper 95% CI |
|---|---|---|---|
| November 2024 | 519.14 units | 461.47 | 576.8 |
| December 2024 | 518.22 units | 459.93 | 576.51 |
| January 2025 | 517.47 units | 458.77 | 576.18 |
| February 2025 | 516.86 units | 457.89 | 575.84 |
| March 2025 | 516.37 units | 457.21 | 575.52 |
| April 2025 | 515.96 units | 456.69 | 575.24 |
Model Metrics
| AIC: | 190.8567 |
|---|---|
| BIC: | 194.6344 |
| Observations ($n$): | 19 |
| Error variance ($\sigma^2$): | 837.5494 |
Lower AIC/BIC indicates a better fit-versus-complexity trade-off.
Out-of-Sample Accuracy
| MAE: | 17.68 units |
|---|---|
| RMSE: | 20.04 units |
| MAPE: | 3.53% |
| Train / Test Periods: | 14 / 5 |
Accurate Forecast (MAPE < 10%)
Measured on periods the model never saw during fitting. Full accuracy breakdown →