Vector (FSharp.Stats) | FSharp.Stats

FSharp.Stats

Vector Module

Namespace: FSharp.Stats
Assembly: FSharp.Stats.dll
Parent Module: Correlation

Contains correlation functions optimized for vectors

Functions and values

Function or value	Description
`autoCorrelation lag v1` Full Usage: `autoCorrelation lag v1` Parameters: lag : `int` - v1 : `Vector<float>` - Returns: `float`	computes the sample auto correlation (using pearson correlation) of a signal at a given lag. lag : `int` v1 : `Vector<float>` Returns: `float` Example
`autoCovariance lag seq` Full Usage: `autoCovariance lag seq` Parameters: lag : `int` - seq : `Vector<float>` - Returns: `float`	computes the sample auto corvariance of a signal at a given lag. lag : `int` seq : `Vector<float>` Returns: `float` Example
`bicor vec1 vec2` Full Usage: `bicor vec1 vec2` Parameters: vec1 : `Vector<float>` - vec2 : `Vector<float>` - Returns: `float`	Biweighted Midcorrelation. This is a median based correlation measure which is more robust against outliers. vec1 : `Vector<float>` vec2 : `Vector<float>` Returns: `float` Example
`correlationOf corrF lag v1 v2` Full Usage: `correlationOf corrF lag v1 v2` Parameters: corrF : `Vector<float> -> Vector<float> -> float` - lag : `int` - v1 : `Vector<float>` - v2 : `Vector<float>` - Returns: `float`	computes the sample correlation of two signal at a given lag. was tested in comparison to: https://www.wessa.net/rwasp_autocorrelation.wasp corrF : `Vector<float> -> Vector<float> -> float` lag : `int` v1 : `Vector<float>` v2 : `Vector<float>` Returns: `float` Example
`normalizedXCorr lag v1 v2` Full Usage: `normalizedXCorr lag v1 v2` Parameters: lag : `int` - v1 : `Vector<float>` - v2 : `Vector<float>` - Returns: `float`	computes the normalized (using pearson correlation) cross-correlation of signals v1 and v2 at a given lag. lag : `int` v1 : `Vector<float>` v2 : `Vector<float>` Returns: `float` Example
`xCorr lag v1 v2` Full Usage: `xCorr lag v1 v2` Parameters: lag : `int` - v1 : `Vector<float>` - v2 : `Vector<float>` - Returns: `float`	computes the unnormalized (using only the dot product) cross-correlation of signals v1 and v2 at a given lag. lag : `int` v1 : `Vector<float>` v2 : `Vector<float>` Returns: `float` Example