bayes_posterior
std.stats.bayes_posterior · Level L0Bayes' theorem on a finite partition of hypotheses: the posterior P(Hᵢ | E) = P(Hᵢ)·P(E | Hᵢ) / Σⱼ P(Hⱼ)·P(E | Hⱼ). The evidence in the denominator is the law of total probability, and it must be positive.
P(Hᵢ | E) = P(Hᵢ)P(E | Hᵢ) / Σⱼ P(Hⱼ)P(E | Hⱼ)
Signature
bayes_posterior(prior: f64[k], likelihood: f64[k]) → f64[k]
Structure
The function as NOVA stores it: one box per input, operation and output, and arrows that carry values. A double border marks another library function this one runs — called once, or by Scan once per element; select it to open that function.
- input
- operation
- constant
- call
- output
Verification
- Signature proven by NOVA’s shape solver, for every size.
- Equal to the reference
prior*likelihood / sum(prior*likelihood)in exact rational arithmetic, on all 40 test cases. - All 163 float64 results inside the running error bound; the closest uses 45% of it.
- Interpreter and NumPy backend return bit-identical results.
- At float32 too: the 40 test cases rounded to float32, and 40 of them inside the running error bound at u = 2⁻²⁴; the closest uses 42% of it.
Accuracy in detail
- correctly rounded (the float64 nearest the exact value)
- 77%
- bit-equal to the NumPy formula in float64
- 91%
- largest error, in units in the last place
- 2.59
Identity
Calls
—
Called by
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sha256:d6bc74ca8b2d052346ed9abf4a59578dc7c404a75b788213429e44e8b4555597The semantic hash of the graph. It changes when the program changes, and never when only its documentation does.
Control handle
- Symbol
- Ω:std.stats.bayes_posterior · Ω:bayes_posterior
- Pins
sha256:f2b230e80cd6c40d62b9663dfdecf039af1896cf5f79686072aee866c60fdc02this graph alone- Evidence
sha256:8b6b3cec9b9c3717c2d616d99d3257f8ef85949f98765e60ce2ad6da2add6d39the hash of its verification record- Needs
- no capability: a pure function
Through NOVA’s control layer, the symbol launches this function only while the program still matches what it pins: a change to this graph, or to any graph it reaches, needs a migration first.