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lib/numerics/tdist/Tdist.md

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 # TDIST: Student's t-Distribution CDF
 
+| Property         | Value                            |
+| ---------------- | -------------------------------- |
+| **Category**     | Numeric                        |
+| **Inputs**       | Source (close)                          |
+| **Parameters**   | `nu` (default 10), `period` (default 14)                      |
+| **Outputs**      | Single series (Tdist)                       |
+| **Output range** | Varies (see docs)                     |
+| **Warmup**       | `period` bars                          |
+
+### TL;DR
+
+- The Student's t-Distribution CDF transforms a min-max normalized price into the cumulative distribution function of Student's t-distribution, produ...
+- Parameterized by `nu` (default 10), `period` (default 14).
+- 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 Student's t-Distribution CDF transforms a min-max normalized price into the cumulative distribution function of Student's t-distribution, producing an output in $[0, 1]$. The t-distribution is the normal distribution's heavier-tailed cousin: as degrees of freedom $\nu$ increase, it converges to the Gaussian; at low $\nu$ it accommodates extreme values that the normal distribution would assign negligible probability. The implementation normalizes price to $[0, 1]$, maps to a t-statistic via linear scaling to $[-3, +3]$, then evaluates the CDF through the regularized incomplete beta function. This makes TDIST a robust percentile ranking that is less sensitive to outliers than NORMDIST.
 
 ## Historical Context