2005-2006 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe
The validity of any test for nonlinearity based on resampling techniques depends heavily on the cons...
The performance of recurrence networks and symbolic networks to detect weak nonlinearities in time ...
In this article we propose a quick, efficient, and easy method to detect whether a time series Yt po...
In the analysis of real world data, the surrogate data test is often performed in order to investiga...
When dealing with measured data from dynamic systems we often make the tacit assumption that the dat...
Most statistical signal nonlinearity analyses adopt the Monte-Carlo approach proposed by Theiler an...
Surrogate data methods have been widely applied to produce synthetic data, while maintaining the sam...
We describe an approach for evaluating the statistical significance of evidence for nonlinearity in ...
The schemes for the generation of surrogate data in order to test the null hypothesis of linear stoc...
We review a relatively new statistical test that may be applied to determine whether an observed tim...
Abstract—We review a relatively new statistical test that may be applied to determine whether an obs...
2006-2007 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe
The availability of time series of the evolution of the properties of physical systems is increasing...
In this chapter, we review the problem of testing for nonlinearity in time series. First, we discuss...
We introduce a statistical method to detect nonlinearity and nonstationarity in time series, that wo...
The validity of any test for nonlinearity based on resampling techniques depends heavily on the cons...
The performance of recurrence networks and symbolic networks to detect weak nonlinearities in time ...
In this article we propose a quick, efficient, and easy method to detect whether a time series Yt po...
In the analysis of real world data, the surrogate data test is often performed in order to investiga...
When dealing with measured data from dynamic systems we often make the tacit assumption that the dat...
Most statistical signal nonlinearity analyses adopt the Monte-Carlo approach proposed by Theiler an...
Surrogate data methods have been widely applied to produce synthetic data, while maintaining the sam...
We describe an approach for evaluating the statistical significance of evidence for nonlinearity in ...
The schemes for the generation of surrogate data in order to test the null hypothesis of linear stoc...
We review a relatively new statistical test that may be applied to determine whether an observed tim...
Abstract—We review a relatively new statistical test that may be applied to determine whether an obs...
2006-2007 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe
The availability of time series of the evolution of the properties of physical systems is increasing...
In this chapter, we review the problem of testing for nonlinearity in time series. First, we discuss...
We introduce a statistical method to detect nonlinearity and nonstationarity in time series, that wo...
The validity of any test for nonlinearity based on resampling techniques depends heavily on the cons...
The performance of recurrence networks and symbolic networks to detect weak nonlinearities in time ...
In this article we propose a quick, efficient, and easy method to detect whether a time series Yt po...
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