This screencast shows  how to use kSpectra for SSA prediction of noisy and short time series. It follows example included with the demo version. Cross-validation is demonstrated to choose optimum number of SSA components for prediction, and to provide estimates of the forecast skill.  Editing of multiple plots is shown, including browsing, in/out zooming and cropping. 

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This screencast shows how to apply SSA to multivariate data with gaps, following example included with the demo version. Cross-validation is used to find optimum number of SSA components to fill-in the missing values with the “smooth” component,  and to provide estimates of the reconstruction error.  Managing and editing of multiple plots with the help of  Plots Gallery is demonstrated.

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SSA Prediction

Multivariate Gap-Filling

This screencast shows how kSpectra can be used to identify presence and frequency of quasi-periodic oscillatory mode embedded in short sample of red noise with large amplitude. It follows Small Signal example included with the demo version. Different spectral estimation tools are demonstrated, as well as editing of plots.

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Small Signals Finder

Basic Demo

This screencast shows how to apply different spectral estimation tools, including SSA-MEM filtering of noise, as well as various functions of Data I/O, Utilities and plotting, by using Climate example included with the demo version.

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