correlation
std.stats.correlation · Level L1Pearson correlation of two paired samples. Calls covariance and std.
cov(x, y) / (σₓ·σᵧ)
Signature
correlation(x: f64[n], y: f64[n]) → f64[]
Requires: n ≥ 2
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 with n ≥ 2.
- Agrees with the reference
np.corrcoef(x, y)[0, 1]to 80 digits (100-digit arithmetic), on all 40 test cases. - All 40 float64 results inside the running error bound; the closest uses 9% of it.
- Interpreter and NumPy backend return bit-identical results.
Accuracy in detail
- correctly rounded (the float64 nearest the exact value)
- 50%
- bit-equal to the NumPy formula in float64
- 70%
- largest error, in units in the last place
- 1.87
Identity
sha256:b9ee5479ce5ccc1616d0e2fa81effd419febbd58132c8480eb7949929ed74c4aThe semantic hash of the graph. It changes when the program changes, and never when only its documentation does.
Control handle
- Symbol
- Ω:std.stats.correlation · Ω:correlation
- Pins
sha256:dd82c9c2ca5d03a114cbf858abf330d25c5bc99df69e8188c32901dd100f6768this graph and the 3 it reaches through calls- Evidence
sha256:8a6bc5b624c9e9dd7f9117571ff6f2b75a93a30a346537b48f4bedfff764b11ethe 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.