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Miha Kralj
2026-03-13 13:47:10 -07:00
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lib/errors/mse/Mse.md
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@@ -13,9 +13,7 @@
| **PineScript** | [mse.pine](mse.pine) |
- Mean Squared Error (MSE) measures the average of the squares of the errors between actual and predicted values.
- Parameterized by `period`.
- Output range: $\geq 0$.
- Requires 1 bar of warmup before first valid output (IsHot = true).
- **Similar:** [RMSE](../rmse/Rmse.md), [MAE](../mae/Mae.md) | **Trading note:** Mean Squared Error; penalizes large errors quadratically. Standard loss function in regression.
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
Mean Squared Error (MSE) measures the average of the squares of the errors between actual and predicted values. By squaring errors, MSE penalizes large deviations more heavily than small ones.
@@ -147,4 +145,4 @@ RMSE has the advantage of being in the same units as the original data.
* [MAE](../mae/Mae.md) - Mean Absolute Error (robust to outliers)
* [RMSE](../rmse/Rmse.md) - Root Mean Squared Error (same units as data)
* [Huber](../huber/Huber.md) - Combines MSE and MAE benefits
* [Huber](../huber/Huber.md) - Combines MSE and MAE benefits