# roughness_K

From FKSUM v0.1.4
by David Hofmeyr

##### Kernel roughness

Computes the squared L2 norm, also known as the roughness, of a kernel implemented in FKSUM based on its beta coefficients. NB: the coefficients will first be normalised so that the kernel represents a density function. Equivalent to norm_K()^2

- Keywords
- file

##### Usage

`roughness_K(beta)`

##### Arguments

- beta
numeric vector of positive coefficients.

##### Value

positive numeric representing the squared L2 norm, or roughness of the kernel with coefficients beta/norm_const(beta).

##### References

Hofmeyr, D.P. (2019) "Fast exact evaluation of univariate kernel sums", *IEEE Transactions on Pattern Analysis and Machine Intelligence*, in press.

*Documentation reproduced from package FKSUM, version 0.1.4, License: GPL*

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