| Program Name |
Program Description |
Corresponding Octave Function |
Comments
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| arima-model |
Fit and possibly iterate an ARIMA model |
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| ar-model |
Fit and possibly iterate an Autoregessive model |
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| ar-run |
Iterate an Autoregessive model |
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| av-d2 |
Simply smooth output of d2 |
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| boxcount |
Renyi Entopies of Qth order |
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| c1 |
Fixed mass estimation of D1 |
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| c2d |
Get local slopes from correlation integral |
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| c2g |
Gaussian kernel of C2 |
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| c2t |
Takens estimator of D2 |
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| choose |
Choose rows and/or columns from a data file |
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| compare |
Compares two data sets |
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| corr |
Autocorrelation function |
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| d2 |
Correlation dimension d2 |
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| delay |
Creates delay embedding |
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| endtoend |
Determine end-to-end mismatch |
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| events |
Interval/event conversion |
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| extrema |
Determine the extrema of a time series |
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| false_nearest |
The false nearest neighbor algorithm |
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| ghkss |
Nonlinear noise reduction |
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| henon |
Create a Hénon time series |
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| histogram |
Creates histograms |
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| ikeda |
Create an Ikeda time series |
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| intervals |
Event/intervcal conversion |
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| lazy |
Simple nonlinear noise reduction |
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| lfo-ar |
Locally first order model vs. global AR model (old ll-ar) |
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| lfo-run |
Iterate a locally first order model (old nstep) |
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| lfo-test |
Test a locally first order model (old onestep) |
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| lorenz |
Create a Lorenz time series |
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| low121 |
Time domain low pass filter |
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| lyap_k |
Maximal Lyapunov exponent with the Kantz algorithm |
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| lyap_r |
Maximal Lyapunov exponent with the Rosenstein algorithm |
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| lyap_spec |
Full spectrum of Lyapunov exponents |
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| lzo-gm |
Locally zeroth order model vs. global mean |
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| lzo-run |
Iterate a locally zeroth order model |
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| lzo-test |
Test a locally zeroth order model (old zeroth) |
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| makenoise |
Produce noise |
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| mem_spec |
Power spectrum using the maximum entropy principle |
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| mutual |
Estimate the mutual information |
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| notch |
Notch filter |
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| nstat_z |
Nonstationarity testing via cross-prediction |
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| pca |
Principle component analysis |
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| poincare |
Create Poincaré sections |
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| polyback |
Fit a polynomial model (backward elimination) |
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| polynom |
Fit a polynomial model |
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| polynomp |
Fit a polynomial model (reads terms to fit from file) |
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| polypar |
Creates parameter file for polynomp |
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| predict |
Forecast discriminating statistics for surrogates |
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| randomize |
General constraint randomization (surrogates) |
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| randomize_spikeauto_exp_random |
Surrogate data preserving event time autocorrelations |
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| randomize_spikespec_exp_event |
Surrogate data preserving event time power spectrum |
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| rbf |
Radial basis functions fit |
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| recurr |
Creates a recurrence plot |
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| resample |
Resamples data |
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| rescale |
Rescale data set |
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| rms |
Rescale data set and get mean, variance and data interval |
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| sav_gol |
Savitzky-Golay filter |
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| spectrum |
Power spectrum using FFT |
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| spikeauto |
Autocorrelation function of event times |
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| spikespec |
Power spectrum of event times |
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| stp |
Creates a space-time separation plot |
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| surrogates |
Creates surrogate data |
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| timerev |
Time reversal discrimating statistics for surrogates |
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| upo |
Finds unstable periodic orbits and estimates their stability |
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| upoembed |
Takes the output of upo and create data files out of it |
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| wiener |
Wiener filter |
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| xc2 |
Cross-correlation integral |
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| xcor |
Cross-correlations |
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| xrecur |
Cross-recurrence Plot |
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| xzero |
Locally zeroth order cross-prediction
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