Struct PearsonCorrelation

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pub struct PearsonCorrelation;

Expand description

Pearson correlation coefficient.

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impl PearsonCorrelation

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pub fn compute(x: &[f64], y: &[f64]) -> Result<f64, MultivariateError>

Compute Pearson correlation between two equal-length slices.

NaN pairs are deleted pairwise. When either series has zero variance the correlation is undefined and the result is NaN, not 0.0 — the convention RollingCorrelation and rolling_corr, applied here for the same reason: 0.0 asserts “these series are uncorrelated” where the truth is “there is nothing to correlate”, and a caller acts on the first.

§Errors

MultivariateError::DimensionMismatch on unequal lengths, and MultivariateError::InsufficientData with fewer than two usable pairs.

Trait Implementations§

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impl CorrelationMethod for PearsonCorrelation

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fn compute(&self, x: &[f64], y: &[f64]) -> Result<f64, MultivariateError>

Compute the correlation coefficient between two equal-length slices.

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fn supports_incremental(&self) -> bool

Whether this method supports incremental (online) updates.

Auto Trait Implementations§

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impl UnwindSafe for PearsonCorrelation

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impl<T> Allocation for T
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impl<T> From<T> for T

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