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22 lines
1.4 KiB
Markdown
22 lines
1.4 KiB
Markdown
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# Semantic Description of `obistats` Package
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The `obistats` package provides numerically stable statistical utilities for combinatorics and log-space arithmetic, primarily intended for use in bioinformatics or probabilistic modeling.
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- **`Lchoose(n, x int) float64`**:
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Computes the natural logarithm of the binomial coefficient "n choose x" using the log-gamma function (`math.Lgamma`). This avoids overflow/underflow inherent in direct computation of large factorials.
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- **`Choose(n, x int) float64`**:
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Returns the (floating-point approximation of the) binomial coefficient by exponentiating `Lchoose`. *Note*: The argument order in the implementation (`math.Exp(Lchoose(x,n))`) appears reversed—likely a typo; should be `Lchoose(n,x)`.
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- **`LogAddExp(x, y float64) float64`**:
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Computes `log(exp(x) + exp(y))` in a numerically stable way. Uses the identity:
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`log(eˣ + eʸ) = max(x, y) + log(1 + exp(-|x - y|))`, implemented via `math.Log1p` for precision near zero.
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Handles NaNs/infinities with logging and fallback.
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All functions rely on `math` for core operations, and use Logrus (`log.Errorf`) to warn about invalid inputs (e.g., non-finite values).
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Use cases include:
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- Exact p-value computation in overrepresentation tests (e.g., hypergeometric),
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- Log-probability accumulation in hidden Markov models or Bayesian networks,
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- Stable mixture model likelihood evaluations.
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