TOCSY - Toolboxes for Complex Systems: The NESToolbox is a collection of algorithms to perform similarity estimation for irregularly sampled time series as they arise for example in the geosciences. It is implemented as a toolbox for the widely used software MATLAB and the freely available open-source software OCTAVE. At the center of the toolbox are the functions for linear and nonlinear similarity estimation for irregular time series, which are based on Gaussian-kernel weight functions. Cross-correlation estimation, as it is used in most standard time series analysis, cannot be performed for irregular time series directly, as the vector index cannot be used as a substitute for time differences. The conventional approach, interpolation of the time series to regular grid followed by the use of standard estimators, has bias side effects . The function similarity.m makes alternative approaches such as the Gaussian-kernel-based cross correlation , the nonlinear Gaussian-kernel-based mutual information  or the Event Synchronization function  available under a single, unified syntax. Additional functions allow for the estimation of uncorrelated time series surrogates to test the significance of similarity estimates as well as nonlinear trends, power spectra and weighted scatterplots. The usage of these functions is illustrated in the script test_nest.m, and a list of the available functions can be found in Contents.m
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References in zbMATH (referenced in 1 article )
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- Ólafsdóttir, K.B.; Mudelsee, M.: More accurate, calibrated bootstrap confidence intervals for estimating the correlation between two time series (2014)