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Eric Coissac
8c7017a99d
- Update obioptions.Version from "Release 4.4.29" to "/v/ Release v5" - Update version.txt from 4.29 → .30 (automated by Makefile)
31 lines
1.6 KiB
Markdown
31 lines
1.6 KiB
Markdown
# `obistats` Package: Normal Distribution Utilities
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The `obistats` package provides a lightweight, efficient implementation of the **normal (Gaussian) distribution**, including core statistical operations.
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## Core Type
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- `NormalDist`: Represents a normal distribution with parameters:
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- `Mu` (mean)
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- `Sigma` (standard deviation)
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## Predefined Constants
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- `StdNormal`: A standard normal distribution (`Mu = 0`, `Sigma = 1`).
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- `invSqrt2Pi`: Precomputed constant for performance optimization.
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## Key Methods
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| Method | Description |
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|--------|-------------|
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| `PDF(x)` | Computes the **probability density function** at point `x`. |
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| `pdfEach(xs [])` | Vectorized PDF evaluation over a slice of values (optimized for standard normal). |
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| `CDF(x)` | Computes the **cumulative distribution function** at point `x` via error function (`erfc`). |
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| `cdfEach(xs [])` | Vectorized CDF evaluation over a slice. |
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| `InvCDF(p)` | Computes the **inverse CDF (quantile function)** using Acklam’s algorithm with refinement. Handles edge cases (`p = 0`, `1`) and numerical stability. |
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| `Rand(r *rand.Rand)` | Generates a random sample from the distribution (uses Go’s built-in `NormFloat64`). |
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| `Bounds()` | Returns a practical support interval: `[Mu − 3·Sigma, Mu + 3·Sigma]` (≈99.7% coverage). |
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## Implementation Notes
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- Optimized paths for standard normal (`Mu = 0`, `Sigma = 1`) reduce computation cost.
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- Uses Go’s standard math library (`math.Erfc`, `math.Log`, etc.).
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- Designed for performance and numerical accuracy in statistical applications.
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> *Note: Duplicates functionality from an internal module (`bench`), likely for reuse in public packages.*
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