User:Josiah425:TISEAN Package:Table of functions
In reference to the TISEAN library alphabetical order of programs which is located here.
| Program Name | Program Description | Corresponding Octave Function | Comments |
|---|---|---|---|
| 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 |