We describe a method for investigating nonlinearity in irregular fluctuations (short-term variability) of time series even if the data exhibit long-term trends (periodicities). Such situations are theoretically incompatible with the assumption of previously proposed methods. The null hypothesis addressed by our algorithm is that irregular fluctuations are generated by a stationary linear system. The method is demonstrated for numerical data generated by known systems and applied to several actual time series.Department of Electronic and Information Engineerin
We develop a test of the null hypothesis that an observed time series is a realization of a strictly...
This article aims at constructing a new method for testing the statistical significance of seasonal ...
We consider the limitations of two techniques for detecting nonlinearity in time series. The rst tec...
Abstract—We describe a method for investigating non-linearity in irregular fluctuations of time seri...
2006-2007 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe
Detection of nonlinearity in experimental time series is usually based on rejection of a linear null...
In this chapter, we review the problem of testing for nonlinearity in time series. First, we discuss...
We describe an approach for evaluating the statistical significance of evidence for nonlinearity in ...
The complexity of RR variability is approached in the short and in the long term by means of black-b...
2006-2007 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe
: This paper reports on the application to field measurements of time series methods developed on th...
How can fluctuations in one-dimensional time series data be characterized and how can detected effec...
We introduce a statistical method to detect nonlinearity and nonstationarity in time series, that wo...
Nonlinear times series properties are represented by the Fourier phases of the time series and for a...
This thesis presents methods of testing the periodicity and trend for the time series, which exhibit...
We develop a test of the null hypothesis that an observed time series is a realization of a strictly...
This article aims at constructing a new method for testing the statistical significance of seasonal ...
We consider the limitations of two techniques for detecting nonlinearity in time series. The rst tec...
Abstract—We describe a method for investigating non-linearity in irregular fluctuations of time seri...
2006-2007 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe
Detection of nonlinearity in experimental time series is usually based on rejection of a linear null...
In this chapter, we review the problem of testing for nonlinearity in time series. First, we discuss...
We describe an approach for evaluating the statistical significance of evidence for nonlinearity in ...
The complexity of RR variability is approached in the short and in the long term by means of black-b...
2006-2007 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe
: This paper reports on the application to field measurements of time series methods developed on th...
How can fluctuations in one-dimensional time series data be characterized and how can detected effec...
We introduce a statistical method to detect nonlinearity and nonstationarity in time series, that wo...
Nonlinear times series properties are represented by the Fourier phases of the time series and for a...
This thesis presents methods of testing the periodicity and trend for the time series, which exhibit...
We develop a test of the null hypothesis that an observed time series is a realization of a strictly...
This article aims at constructing a new method for testing the statistical significance of seasonal ...
We consider the limitations of two techniques for detecting nonlinearity in time series. The rst tec...