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4.9 | 7 ratings Rate this file 12 Downloads (last 30 days) File Size: 93.1 KB File ID: #19148 Version: 1.0

hurst parameter estimate

by

Chu Chen (view profile)

 

11 Mar 2008 (Updated )

This routine estimate the long-range dependence of a sequence with several methods.

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Description

The most important characteristic of a covariance stationary self-similar stochastic process is that it is long-range dependent. The long-range dependent time series hold significant correlations across arbitrarily large time scales. And the Hurst parameter H measure the degree of long-range dependence and can be estimated by several methods.

MATLAB release MATLAB 7.1.0 (R14SP3)
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Comments and Ratings (12)
09 Sep 2016 zinat bahrami

Hi chu.

What methods have you used to generate the input sequence?I have used your codes, and in higuchi methode I found hurst parameter greater than 1 and in more methods I found hurst parameter least than 0.5.please tell me why?thanks

15 Jun 2016 Grace Pan

hi chu,
I had some H greater than 1 when i run this code. could you tell why? thx

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15 Dec 2014 Markus Gschwind

Great peace of code! I was looking long time around to find it.
- Maybe the various methods could briefly be summarized so that terminological variations can be cleared.

15 Apr 2012 Alex Wong

Hi Chu,

I would like to estimate the Hurst coefficient so I can determine if my data series is persistent (H>0.5), antipersistent (H<0.5), or neutral (H=0.5). Several of the estimates I get are, for example, H = 1.8, or H=1.6, H=0.9....should I disregard the whole number and concentrate only on the decimals for interpreting persistence?

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12 Mar 2011 henry gorx

great¡, it works very well.

08 Mar 2011 saca 2009

while running the program graph is not coming it is showing error that undefined isplot so kindly suggest me how can i over come this error

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23 Aug 2010 Washington

I have used your RS routine, and in some cases I found hurst parameter greater than 1 (one), is it anything wrong? Thanks.

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25 May 2010 zheng zhilong  
06 Jan 2010 zhang bin

Thanks a lot! Very good!

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28 Nov 2009 Felipe Ardila

Good job, usefull package to esitmate Hurst coef, thanks

15 Aug 2009 Tom Wei

very good, and contain different methods to estimate hurst parameter

15 Oct 2008 Alexandre Budoudoo

A very good package combining different methods. Recommended for studing purposes and developpment of own algorithms

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