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Miha Kralj
2026-03-13 13:47:10 -07:00
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lib/errors/rsquared/Rsquared.md
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| **PineScript** | [rsquared.pine](rsquared.pine) |
- The Coefficient of Determination (R²) measures the proportion of variance in the actual values that is predictable from the predicted values.
- Parameterized by `period`.
- Output range: $(-\infty, 1]$.
- Requires `period` bars of warmup before first valid output (IsHot = true).
- **Similar:** [RSE](../rse/Rse.md), [Correlation](../../statistics/correlation/Correlation.md) | **Trading note:** R-squared (coefficient of determination); 1.0 = perfect fit, 0 = no better than mean.
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
The Coefficient of Determination (R²) measures the proportion of variance in the actual values that is predictable from the predicted values. R² ranges from negative infinity to 1, where 1 indicates perfect predictions.
@@ -149,4 +147,4 @@ Rsquared.Batch(actualSpan, predictedSpan, outputSpan, 14);
* **Use R²** when you want an intuitive measure of model quality (0-1 scale for good models)
* **Use RSE** when you want to compare error magnitudes directly
* **Use both** to get complementary perspectives on model performance
* **Use both** to get complementary perspectives on model performance