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autocorr Class Reference

Calculate the autocorrelation function for a vector. More...

#include <autocorr.h>

List of all members.

Public Methods
	autocorr (double lim=0.01, size_t numPts=32)
	~autocorr ()
void	ACF (const double *v, const size_t N, acorrInfo &info)
	Calculate the autocorrelation function. More...
Private Methods
	autocorr (const autocorr &rhs)
void	acorrSlope (acorrInfo &info)
	Calculate the slope the the log of the autocorrelation curve. More...
Private Attributes
const double	limit_
const size_t	numPoints_

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Detailed Description

Calculate the autocorrelation function for a vector.

Copyright and Use

You may use this source code without limitation and without fee as long as you include:

This software was written and is copyrighted by Ian Kaplan, Bear Products International, www.bearcave.com, 2001.

This software is provided "as is", without any warranty or claim as to its usefulness. Anyone who uses this source code uses it at their own risk. Nor is any support provided by Ian Kaplan and Bear Products International.

Please send any bug fixes or suggested source changes to:

     iank@bearcave.com

Definition at line 37 of file autocorr.h.

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Constructor & Destructor Documentation

autocorr::autocorr ( const autocorr & rhs ) [private]

autocorr::autocorr ( double lim = 0.01, size_t numPts = 32 ) [inline]

Definition at line 76 of file autocorr.h. : limit_(lim), numPoints_(numPts) {}

autocorr::~autocorr ( ) [inline]

Definition at line 78 of file autocorr.h. {}

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Member Function Documentation

void autocorr::ACF ( const double * v, const size_t N, acorrInfo & info )

Calculate the autocorrelation function. Definition at line 50 of file autocorr.cpp. { if (! info.points().empty() ) { info.points().clear(); } // The devMean array will contain the deviation from the mean. // That is, v[i] - mean(v). double *devMean = new double[ N ]; double sum; size_t i; // Calculate the mean and copy the vector v, into devMean sum = 0; for (i = 0; i < N; i++) { sum = sum + v[i]; devMean[i] = v[i]; } double mean = sum / static_cast<double>(N); // Compute the values for the devMean array. Also calculate the // denominator for the autocorrelation function. sum = 0; for (i = 0; i < N; i++) { devMean[i] = devMean[i] - mean; sum = sum + (devMean[i]*devMean[i]); } double denom = sum / static_cast<double>(N); // Calculate a std::vector of values which will make up // the autocorrelation function. double cor = 1.0; for (size_t shift = 1; shift <= numPoints_ && cor > limit_; shift++) { info.points().push_back( cor ); size_t n = N - shift; sum = 0.0; for (i = 0; i < n; i++) { sum = sum + (devMean[i] * devMean[i+shift]); } double numerator = sum / static_cast<double>(n) cor = numerator / denom; } // calculate the log/log slope of the autocorrelation acorrSlope( info ); delete [] m; } // ACF

void autocorr::acorrSlope ( acorrInfo & info ) [private]

Calculate the slope the the log of the autocorrelation curve. Autocorrelation is one measure for long memory (long range dependence) in a data set. The idea behind implementing this function was that the slope of the log/log plot of the autocorrelation curve could be compared for various data sets. The Hurst exponent provides another measure for long memory processes. My original idea was to use the slope of the log/log ACF as a comparision for the various Hurst values. As it turned out, the slope of the ACF was not a very useful metric since the slopes did not differ much for various Hurst exponents Definition at line 27 of file autocorr.cpp. Referenced by ACF(). { const size_t len = info.points().size(); if (len > 0) { lregress::lineInfo regressInfo; lregress lr; vector<lregress::point> regressPoints; for (size_t i = 0; i < len; i++) { double x = log(i+1); double y = log((info.points())[i]); regressPoints.push_back( lregress::point(x,y) ); } lr.lr( regressPoints, regressInfo ); info.slope( regressInfo.slope() ); info.slopeErr( regressInfo.slopeErr() ); } } // acorrSlope

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Member Data Documentation

const double autocorr::limit_ [private]

Definition at line 42 of file autocorr.h.

const size_t autocorr::numPoints_ [private]

Definition at line 44 of file autocorr.h.

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The documentation for this class was generated from the following files:

• autocorr.h
• autocorr.cpp

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