**Hurst exponent (H)** determines the rate of chaos

**Lyapunov exponent (L)** determines the rate of predictability

In addition Hurst exponent can distinguish fractal from random time series, or find the long memory cycles.

Will codify both exponents as C++ classes that are generic enough to analyze any data points in lottery time series (ie frequency/number transitions but also others)

If a Hurst exponents is evaluated to a fractal dimension in a lottery time series (key in all this endavour) we will be able to find an attractor and via Lyapunov exponent and multi-fractal and L-variable fractal analysis (the superfractal) try to approximate (an eventually predict) its chaotic "orbits"

For a nice and short explanation on both exponents see ref.1

References:

1. Energy Time Series and Chaos: http://www.iqnet.cz/dostal/CHA2.htm

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