FWHVA-package {FWHVA}R Documentation

Fast calculating the mean degree and mean strength of weighted visibility horizontal graph ~~ package title ~~

Description

Implementation horizontal visiblity graph needs to iterate three variables (i, j and k), which means that the worst computing time to construct a HVG from a time series with n data points is $O(n^3)$.
This algorithm excutes the HVG with $O(n)$ and also include the weighted information.
The limitation, the input length of FWHVA is less than 12193, if the input length is large than it, the stack may be overflow.

Usage

  FWHVA(data)  

Arguments

data input data, one dimension

Details

Package: FWHVA
Type: Package
Version: 1.3
Date: 2014-4-30
License: GPL (version 2 or later)

Value

mean degree
mean strength
Number degree 2
repeat time

Author(s)

Guohun Zhu
Maintainer: Guohun Zhu <zhuguohun@163.com> or <Guohun.Zhu@usq.edu.au>

References

Zhu, Guohun, Li, Yan, & Wen, Peng(Paul). (2012). An Efficient Visibility Graph Similarity Algorithm and Its Application on Sleep Stages Classification. In FabioMassimo Zanzotto, Shusaku Tsumoto, Niels Taatgen & Yiyu Yao (Eds.), Brain Informatics (Vol. 7670, pp. 185-195): Springer Berlin Heidelberg.

and

Guohun Zhu, Yan Li, Peng (Paul) Wen, Epileptic seizure detection in EEGs signals using a fast weighted horizontal visibility algorithm, Computer Methods and Programs in Biomedicine, Available online 15 April 2014, ISSN 0169-2607, http://dx.doi.org/10.1016/j.cmpb.2014.04.001. (http://www.sciencedirect.com/science/article/pii/S0169260714001266)

See Also

HVG ~~ <pkg> ~~ ~~ <FastVG> ~~ ~~ <GraphEntropy> ~~

Examples


a=c(10,8,6,4,2,1,3,5,7,9,11)
FWHVA(a)


[Package FWHVA version 1.3.0 Index]