Bandwidth (FSharp.Stats)

Bandwidth Module

Bandwidth selectors

Modules	Description
BinNumber	Compute the number of bins for a histogram

Function or value	Description
`forHistogram data` Full Usage: `forHistogram data` Parameters: data : `float seq` - Returns: `float`	Simple bandwidth for histogram data : `float seq` Returns: `float` Example
`freedmanDiaconis data` Full Usage: `freedmanDiaconis data` Parameters: data : `float[]` - Returns: `float`	Calcultes bandwidth based on the Freedman–Diaconis rule data : `float[]` Returns: `float` Example
`fromBinNumber min max nBins` Full Usage: `fromBinNumber min max nBins` Parameters: min : `^a` - max : `^b` - nBins : `^c` - Returns: `float` Modifiers: inline Type parameters: ^a, ^b, ^c	Calculates the bandwidth from min max and number of bins min : `^a` max : `^b` nBins : `^c` Returns: `float` Example
`nrd0 x` Full Usage: `nrd0 x` Parameters: x : `float[]` - Returns: `float`	Implements Silverman's ‘rule of thumb’ for choosing the bandwidth of a Gaussian kernel density estimator. x : `float[]` Returns: `float` Example
`scottNormal data` Full Usage: `scottNormal data` Parameters: data : `float[]` - Returns: `float`	Calcultes bandwidth according to Scott's normal reference rule data : `float[]` Returns: `float` Example
`uLSCV data numberOfBins` Full Usage: `uLSCV data numberOfBins` Parameters: data : `float[]` - numberOfBins : `int option` - Returns: `float`	Least squares cross-validation of bandwidth (unbiased) data : `float[]` numberOfBins : `int option` Returns: `float` Example