mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-17 01:58:06 +00:00
doc headers
This commit is contained in:
@@ -1,5 +1,22 @@
|
||||
# TRIM: Trimmed Mean Moving Average
|
||||
|
||||
| Property | Value |
|
||||
| ---------------- | -------------------------------- |
|
||||
| **Category** | Statistic |
|
||||
| **Inputs** | Source (close) |
|
||||
| **Parameters** | `period`, `trimPct` (default 10.0) |
|
||||
| **Outputs** | Single series (Trim) |
|
||||
| **Output range** | Varies (see docs) |
|
||||
| **Warmup** | `period` bars |
|
||||
|
||||
### TL;DR
|
||||
|
||||
- The Trimmed Mean Moving Average computes a rolling average after discarding a configurable percentage of the most extreme values from each tail of ...
|
||||
- Parameterized by `period`, `trimpct` (default 10.0).
|
||||
- Output range: Varies (see docs).
|
||||
- Requires `period` bars of warmup before first valid output (IsHot = true).
|
||||
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
|
||||
|
||||
The Trimmed Mean Moving Average computes a rolling average after discarding a configurable percentage of the most extreme values from each tail of the sorted lookback window. By removing the lowest and highest `trimPct%` of observations, TRIM eliminates the influence of outliers while retaining more information than a pure median. At `trimPct = 0` it degenerates to the SMA; at `trimPct = 50` it becomes the median. The default 10% trim provides a robust central tendency estimator that resists spike contamination with minimal loss of responsiveness, requiring $O(N \log N)$ for the sort plus $O(N)$ for the summation per bar.
|
||||
|
||||
## Historical Context
|
||||
|
||||
Reference in New Issue
Block a user