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Refactor documentation to remove "Zero-Allocation Design" sections across various trend indicators and implement a PowerShell script for automated cleanup
- Updated mathematical foundations and performance profiles where necessary to maintain clarity and coherence.
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@@ -32,19 +32,6 @@ $$ TRIMA = SMA(SMA(Price, P_1), P_2) $$
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## Performance Profile
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### Zero-Allocation Design
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TRIMA relies on two internal `Sma` instances, which use pre-allocated `RingBuffer`s. The chaining of updates is done via value passing, ensuring no intermediate objects are created on the heap.
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| Metric | Score | Notes |
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| :--- | :--- | :--- |
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| **Throughput** | High | 2 SMAs |
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| **Complexity** | O(1) | Constant time update |
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| **Accuracy** | 6/10 | Heavily smoothed, loses detail |
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| **Timeliness** | 4/10 | Significant lag (Lag ≈ N/2 + N/2) |
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| **Overshoot** | 9/10 | Very stable, minimal overshoot |
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| **Smoothness** | 9/10 | Triangular weighting removes high freq noise |
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## Validation
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Validated against TA-Lib (`TA_TRIMA`) and Skender.Stock.Indicators.
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