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docs: fix truncated intro bullets across indicators
151 indicator docs had their intro bullet cut off mid-word with '...'. Completed each with the first sentence of its own intro paragraph.
This commit is contained in:
Miha Kralj
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| **Warmup** | `period` bars |
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| **PineScript** | [maape.pine](maape.pine) |
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- Mean Arctangent Absolute Percentage Error (MAAPE) transforms percentage errors through the arctangent function, naturally bounding the metric betwe...
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- Mean Arctangent Absolute Percentage Error (MAAPE) transforms percentage errors through the arctangent function, naturally bounding the metric between 0 and π/2.
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- **Similar:** [MAPE](../mape/Mape.md), [SMAPE](../smape/Smape.md) | **Trading note:** Mean Arctangent Absolute Percentage Error; bounded and symmetric, handles zero values unlike MAPE.
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- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
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@@ -12,7 +12,7 @@
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| **Warmup** | `period` bars |
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| **PineScript** | [mapd.pine](mapd.pine) |
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- Mean Absolute Percentage Deviation (MAPD) measures the average absolute percentage difference between actual and predicted values, using the predic...
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- Mean Absolute Percentage Deviation (MAPD) measures the average absolute percentage difference between actual and predicted values, using the predicted value as the denominator.
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- **Similar:** [MAPE](../mape/Mape.md), [WMAPE](../wmape/Wmape.md) | **Trading note:** Mean Absolute Percentage Deviation; total absolute error divided by total actual values.
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- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
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@@ -12,7 +12,7 @@
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| **Warmup** | `period + 1` bars |
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| **PineScript** | [mase.pine](mase.pine) |
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- Mean Absolute Scaled Error (MASE) normalizes forecast errors by the average error of a naive "random walk" forecast (using the previous value as th...
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- Mean Absolute Scaled Error (MASE) normalizes forecast errors by the average error of a naive "random walk" forecast (using the previous value as the prediction).
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- **Similar:** [MAE](../mae/Mae.md), [RAE](../rae/Rae.md) | **Trading note:** Mean Absolute Scaled Error; compares forecast to naïve random-walk baseline. <1 = better than naïve.
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- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
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@@ -12,7 +12,7 @@
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| **Warmup** | `period` bars |
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| **PineScript** | [rae.pine](rae.pine) |
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- Relative Absolute Error (RAE) measures the total absolute error of predictions relative to the total absolute error of a simple baseline predictor ...
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- Relative Absolute Error (RAE) measures the total absolute error of predictions relative to the total absolute error of a simple baseline predictor that always predicts the mean of actual values.
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- **Similar:** [MASE](../mase/Mase.md), [MRAE](../mrae/Mrae.md) | **Trading note:** Relative Absolute Error; total absolute error relative to naïve model. <1 = outperforms naïve.
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- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
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@@ -12,7 +12,7 @@
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| **Warmup** | `period` bars |
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| **PineScript** | [rmse.pine](rmse.pine) |
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- Root Mean Squared Error (RMSE) is the square root of MSE, providing an error metric in the same units as the original data while retaining sensitiv...
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- Root Mean Squared Error (RMSE) is the square root of MSE, providing an error metric in the same units as the original data while retaining sensitivity to large errors.
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- **Similar:** [MSE](../mse/Mse.md), [MAE](../mae/Mae.md) | **Trading note:** Root Mean Squared Error; same units as input, emphasizes large deviations. Most common accuracy metric.
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- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
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@@ -12,7 +12,7 @@
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| **Warmup** | `period` bars |
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| **PineScript** | [rse.pine](rse.pine) |
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- Relative Squared Error (RSE) measures the total squared error of predictions relative to the total squared error of a simple baseline predictor tha...
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- Relative Squared Error (RSE) measures the total squared error of predictions relative to the total squared error of a simple baseline predictor that always predicts the mean.
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- **Similar:** [RMSE](../rmse/Rmse.md), [Rsquared](../rsquared/Rsquared.md) | **Trading note:** Relative Squared Error; normalized by variance of actuals. >1 = worse than mean prediction.
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- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
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@@ -12,7 +12,7 @@
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| **Warmup** | `period` bars |
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| **PineScript** | [smape.pine](smape.pine) |
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- Symmetric Mean Absolute Percentage Error addresses a fundamental asymmetry in MAPE: the fact that over-predictions and under-predictions of the sam...
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- Symmetric Mean Absolute Percentage Error addresses a fundamental asymmetry in MAPE: the fact that over-predictions and under-predictions of the same magnitude receive different penalties.
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- **Similar:** [MAPE](../mape/Mape.md), [MAAPE](../maape/Maape.md) | **Trading note:** Symmetric MAPE; bounded 0–200%, handles zeros better than MAPE. Common in forecasting competitions.
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- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
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@@ -12,7 +12,7 @@
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| **Warmup** | `period` bars |
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| **PineScript** | [wrmse.pine](wrmse.pine) |
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- WRMSE extends the classic RMSE by incorporating weights for each observation, enabling analysts to emphasize critical data points such as recent ob...
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- WRMSE extends the classic RMSE by incorporating weights for each observation, enabling analysts to emphasize critical data points such as recent observations, high-volume periods, or specific market regimes.
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- **Similar:** [RMSE](../rmse/Rmse.md), [WMAPE](../wmape/Wmape.md) | **Trading note:** Weighted RMSE; emphasizes accuracy at specific points. Useful for time-decay weighting.
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- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
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