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