In many applications, such as physiology and finance, large time series data bases are to be analyzed requiring the computation of linear, nonlinear and other measures. Such measures have been developed and implemented in commercial and freeware softwares rather selectively and independently. The Measures of Analysis of Time Series (MATS) MATLAB toolkit is designed to handle an arbitrary large set of scalar time series and compute a large variety of measures on them, allowing for the specification of varying measure parameters as well. The variety of options with added facilities for visualization of the results support different settings of time series analysis, such as the detection of dynamics changes in long data records, resampling (surrogate or bootstrap) tests for independence and linearity with various test statistics, and discrimination power of different measures and for different combinations of their parameters. The basic features of MATS are presented and the implemented measures are briefly described. The usefulness of MATS is illustrated on some empirical examples along with screenshots. The analysis of time series involves a range of disciplines, from engineering to economics, and its development spans different aspects of the time series, e.g., analysis in the time and frequency domain, and under the assumption of a stochastic or deterministic process (Box et al.Many developed software products include standard methods of time series analysis. Commercial statistical packages, such as SPSS (SPSS Inc., 2006) and SAS (SAS Institute Inc., 2003), have facilities on time series which are basically implementations of the classical Box-Jenkins approach on non-stationary time series. The commercial computational environments MATLAB (The MathWorks, Inc., 2007) and S-PLUS (Insightful Corp., 2003) provide a number of toolboxes or modules that deal with time series (MATLAB: Financial, Econometrics, Signal Processing, Neural Network and Wavelets, S-PLUS: FinMetrics, Wavelet, EnvironmentalStats). Less standard and more advanced tools of time series analysis can be found in a number of commercial stand-alone software packages developed for more specific uses of time series, and in a few freeware packages mostly offering a set of programs rather than an integrated software, such as the TISEAN package which includes a comprehensive set of methods of the dynamical system approach . Some open-source MATLAB toolkits offer selected methods for analyzing an input time series, such as the time series analysis toolbox TSA Schlögl (2002).In many applications, particularly when the system is rather complex as in seismology, climate, finance and physiology, the development of models from data can be a formidable task. There the interest is rather in compressing the information from a time series to some extracted features or measures that can be as simple as descriptive statistics or as complicated as the goodness of fit of a nonlinear model involving many free parameters. Moreover, the problem at hand may involve a number ...