Numeric algorithms and constants module
#include "diplib/accumulators.h"
dip::CovarianceAccumulator class

CovarianceAccumulator computes covariance and correlation of pairs of samples by accumulating the first two central moments and cross-moments.

Contents

Samples are added one pair at the time, using the Push method. Other members are used to retrieve the results. The accumulator uses a stable algorithm to prevent catastrophic cancellation.

The covariance matrix is formed by

| cov.VarianceX()   cov.Covariance() |
| cov.Covariance()  cov.VarianceY()  |

The Regression method returns the parameters to the least squares fit of the equation \(y = a + bx\) , where \(x\) is the first sample in each pair and \(y\) is the second (this is linear regression), \(a\) is the intercept and \(b\) is the slope. The Slope method computes only the slope component.

It is possible to accumulate samples in different objects (e.g. when processing with multiple threads), and add the accumulators together using the + operator.

Aliases

using RegressionResult = dip::RegressionParameters
Copying type for backward compatibility.

Functions

void Reset()
Reset the accumulator, leaving it as if newly allocated.
void Push(dip::dfloat x, dip::dfloat y)
Add a pair of samples to the accumulator
auto Number() const -> dip::uint
Number of samples
auto MeanX() const -> dip::dfloat
Unbiased estimator of population mean for first variable
auto MeanY() const -> dip::dfloat
Unbiased estimator of population mean for second variable
auto VarianceX() const -> dip::dfloat
Unbiased estimator of population variance for first variable
auto VarianceY() const -> dip::dfloat
Unbiased estimator of population variance for second variable
auto StandardDeviationX() const -> dip::dfloat
Estimator of population standard deviation for first variable (it is not possible to derive an unbiased estimator)
auto StandardDeviationY() const -> dip::dfloat
Estimator of population standard deviation for second variable (it is not possible to derive an unbiased estimator)
auto Covariance() const -> dip::dfloat
Unbiased estimator of population covariance
auto Correlation() const -> dip::dfloat
Estimator of correlation between the two variables
auto Slope() const -> dip::dfloat
Computes the slope of the regression line
auto Regression() const -> dip::CovarianceAccumulator::RegressionResult
Computes the slope and intercept of the regression line

Operators

auto operator+=(dip::CovarianceAccumulator const& other) -> dip::CovarianceAccumulator&
Combine two accumulators