an analysis software with souce code for the time series with methods based on the theory of nonline

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				Example: avoiding periodicity artefacts
				
				
				
				
				
				
				
				      
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				Example: avoiding periodicity artefacts
				
				 
				Figure:  
				   Progressive stages of the simulated annealing scheme. The data used in
				   Fig. 6 is used to generate an annealed surrogate that minimises
				    over all
				   permutations of the data. From top to bottom, the values for E are: 0
				   (original data), 1.01 (random scramble), 0.51, 0.12, 0.015, and 0.00013.
				
				
				Let us illustrate the use of the annealing method in the case of the standard
				null hypothesis of a rescaled linear process. We will show how the periodicity
				artefact discussed in Sec. 4.5 can be avoided by using a more
				suitable cost function. We prepare a surrogate for the data shown in
				Fig. 6 (almost unstable AR(2) process) without truncating its
				length. We minimise the cost function given by Eq.(23), involving
				all lags up to . Also, we excluded the first and
				last points from permutations as a cheap way of imposing the long range
				correlation. In Fig. 11 we show progressive stages of the
				annealing procedure, starting from a random scramble. The temperature T is
				decreased by 0.1% after either  permutations have been tried or 
				have been successful.  The final surrogate neither has spuriously matching ends
				nor the additional high frequency components we saw in Fig. 6. The
				price we had to pay was that the generation of one single surrogate took 6 h of
				CPU time on a Pentium II PC at 350 MHz.  If we had taken care of the long range
				correlation by leaving the end points loose but taking , convergence would have been prohibitively slow.  Note that for a
				proper test, we would need at least 19 surrogates. We should stress that this
				example with its very slow decay of correlations is particularly nasty -- but
				still feasible. Obviously, sacrificing 10% of the points to get rid of the
				end point mismatch is preferable here to spending several days of CPU time
				on the annealing scheme. In other cases, however, we may not have such a
				choice.
				
				     
				 Next: Combinatorial minimisation and accuracy
				Up: General constrained randomisation
				 Previous: Computational issues of simulated 
				
				Thomas Schreiber 
				Mon Aug 30 17:31:48 CEST 1999
				
				
				
							

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