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|lazy || Simple nonlinear noise reduction || There is not || FORTRAN
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|lfo-ar || Locally first order model vs. global AR model (old ll-ar) || Does not exist ||C
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|lfo-run || Iterate a locally first order model (old nstep) || Does not exist ||C
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|lfo-test || Test a locally first order model (old onestep) || Does not exist ||C
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|lorenz || Create a Lorenz time series || ||
|low121 || Time domain low pass filter || ||
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|lyap_k || Maximal Lyapunov exponent with the Kantz algorithm || Does not exist ||C
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|lyap_r || Maximal Lyapunov exponent with the Rosenstein algorithm || Does not exist ||C
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|lyap_spec || Full spectrum of Lyapunov exponents || Does not exist ||C
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|lzo-gm || Locally zeroth order model vs. global mean || Does not exist ||C
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|lzo-run || Iterate a locally zeroth order model || Does not exist ||C
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|lzo-test || Test a locally zeroth order model (old zeroth) || Doest not exist ||C
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|makenoise || Produce noise || ||
|poincare || Create Poincaré sections || ||
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|polyback || Fit a polynomial model (backward elimination) || polyfit, detrend, wpolyfit ||I do not know if they work the same way, but it does seem so, written in C
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|polynom || Fit a polynomial model || same as above ||same as above
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|polynomp || Fit a polynomial model (reads terms to fit from file) || same as above ||same as above
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|polypar || Creates parameter file for polynomp || same as above ||same as above
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|predict || Forecast discriminating statistics for surrogates || Does not exist || FORTRAN
|randomize_spikespec_exp_event || Surrogate data preserving event time power spectrum || ||
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|rbf || Radial basis functions fit || Does not exist ||C
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|recurr || Creates a recurrence plot || ||
|xrecur || Cross-recurrence Plot || ||
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|xzero || Locally zeroth order cross-prediction|| Does not exist || C
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