The Delay Vector Variance (DVV) method uses local predictibility in phase space to examine the determinism and nonlinearity within signals. It yields DVV plots in which the target variance is plotted as a standardised distance. DVV scatter plots can also be generated, where the horizontal axis corresponds to the original time series while the vertical axis to that of surrogate series; nonlinearity within the signal can be detected if the scatter plot deviates from the bisector line. This toolbox implements the DVV method in terms of nonlinearity testing for some basic signals. A Delay Vector Variance (DVV) toolbox for MATLAB (c) Copyright Danilo P. Mandic 2008 http://www.commsp.ee.ic.ac.uk/~mandic/dvv.htm The following Matlab files are used to perform DVV and demonstrate its operation: - analysis.m Matlab code to perform the DVV analysis for the case studies stored in *.mat files - dvv.m Implementation of the DVV method for real valued and complex signals - surrogate.m Matlab code which generates surrogate data for real and complex signals ar.mat Stored linear AR2 Signal wind.mat Stored 2D wind Signal henon.mat Stored nonlinear henon map signal