INPUTES: y: y is vector of values(time series data) tau: embedding lag of state space reconstruction. When you have not any information about tau please let it zero. The code will calculates the tau. m: m is embedding dimension. If you have not any information about embedding dimension please let it zero. the code will find proper embedding dimension. OUTPUTS: LLE: Largest Lyapunov Exponent lambda: Lyapunov exponents for various ks. Plot of this exponents is very helpful. If embedding dimension be selected correctly lambda curve will have smooth part(or fairly horizontal). If there is no smooth section on the curve, it is better you try with other embedding dimensions.

lyaprosen.m

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