Selfis

SELFIS (SELF-similarity analysIS) is a java-based software tool for self-similarity and long-range dependence analysis. It is freely distributed as a service to the community. For more information please refer to the corresponding papers and read the short tutorial of SELFIS. Currently, it incorporates various long-range dependence estimation methodologies and the bucket shuffling methodology for long-range dependence detection. Future releases will include time-series processing algorithms and transforms, such as wavelets, Fourier transform, stationarity tests and smoothing algorithms. In addition, the next release will include FGN and FARIMA processes generators to simulate long-range dependence in time-series. Supported Features: Hurst Exponent Estimators: Absolute Value; Aggregate Variance; R/S; Variance of Residuals; Periodogram; Whittle; Abry-Veitch. Bucket shuffling methodology: Internal Shuffling; External Shuffling; 2-Level Shuffling. Other: Autocorrelation Function (ACF); Power Spectrum; Basic statistics (Mean, Std, Variance, Skewness, Kurtosis).