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− | + | In reference to the TISEAN library alphabetical order of programs which is located [http://www.mpipks-dresden.mpg.de/~tisean/Tisean_3.0.1/docs/alphabetical.html| here]. | |

− | In reference to the TISEAN library alphabetical order of programs which is located [http://www.mpipks-dresden.mpg.de/~tisean/Tisean_3.0.1/docs/alphabetical.html here]. | ||

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{| class="wikitable" | {| class="wikitable" | ||

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− | | | + | ! Program Name !! Program Description !! Corresponding Octave Function !! Comments |

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− | + | | arima-model || Fit and possibly iterate an ARIMA model || There is 'aar' in TSA but cannot determine if this is different or not || This is a c-file that can be wrapped in C++/mfile/octfile code | |

− | + | |- | |

+ | |ar-model || Fit and possibly iterate an Autoregessive model || Same as above || C; see also: aarmam, adim, amarma, mvaar from TSA | ||

+ | |- | ||

+ | |ar-run || Iterate an Autoregessive model || Same as above || FORTRAN | ||

+ | |- | ||

+ | |av-d2 || Simply smooth output of d2 || Same as above || C | ||

+ | |- | ||

+ | |boxcount || Renyi Entopies of Qth order || There most likely is none || C | ||

+ | |- | ||

+ | |c1 || Fixed mass estimation of D1 || Most likely is none || FORTRAN | ||

+ | |- | ||

+ | |c2d || Get local slopes from correlation integral || Most likely none || FORTRAN | ||

+ | |- | ||

+ | |c2g || Gaussian kernel of C2 || Does not exist || FORTRAN | ||

+ | |- | ||

+ | |c2t || Takens estimator of D2 || Most likely 'rmle' from tsa || FORTRAN | ||

+ | |- | ||

+ | |choose || Choose rows and/or columns from a data file || Does not need to be ported || ------ | ||

+ | |- | ||

+ | |compare || Compares two data sets || If 'rms' exists in Octave no need for port || FORTRAN | ||

+ | |- | ||

+ | |corr, autocorr || Autocorrelation function || There is 'acorf' in tsa but i don't know if is the same || corr -C, autocorr (faster according to documentation) - FORTRAN | ||

+ | |- | ||

+ | |d2 || Correlation dimension d2 || I believe not, don't know || c | ||

+ | |- | ||

+ | |delay || Creates delay embedding || Most likely does not exist || C | ||

+ | |- | ||

+ | |endtoend || Determine end-to-end mismatch || Does not exist || FORTRAN | ||

+ | |- | ||

+ | |events || Interval/event conversion || Might exist, most likely does not || FORTRAN to be implemented as mfile | ||

+ | |- | ||

+ | |extrema || Determine the extrema of a time series || A min or max function exist, though I do not know if it accomplishes the same task || C | ||

+ | |- | ||

+ | |false_nearest || The false nearest neighbor algorithm || Does not exist || C | ||

+ | |- | ||

+ | |ghkss || Nonlinear noise reduction || There is not || C | ||

+ | |- | ||

+ | |henon || Create a Hénon time series || There is not || To m-file; already ported | ||

+ | |- | ||

+ | |histogram || Creates histograms || Might exist, cannot find(obviously histogram exists, but I cannot tell if it "estimates the scalar distribution of data set") || C | ||

+ | |- | ||

+ | |ikeda || Create an Ikeda time series || Does not exist || FORTRAN to be reimplemented as mfile | ||

+ | |- | ||

+ | |intervals || Event/intervcal conversion || Might exist under different name || FORTRAN to be reimplemented as mfile | ||

+ | |- | ||

+ | |lazy || Simple nonlinear noise reduction || There is not || FORTRAN | ||

+ | |- | ||

+ | |lfo-ar || Locally first order model vs. global AR model (old ll-ar) || Does not exist || C | ||

+ | |- | ||

+ | |lfo-run || Iterate a locally first order model (old nstep) || Does not exist || C | ||

+ | |- | ||

+ | |lfo-test || Test a locally first order model (old onestep) || Does not exist || C | ||

+ | |- | ||

+ | |lorenz || Create a Lorenz time series || Does not exist || FORTRAN | ||

+ | |- | ||

+ | |low121 || Time domain low pass filter || There are lowpass filters in Octave: buttap, cheb1ap, cheb2ap, ellipap, sftrans, but I don't think they perform this task || C, might be ok to implement as mfile | ||

+ | |- | ||

+ | |lyap_k || Maximal Lyapunov exponent with the Kantz algorithm || Does not exist || C | ||

+ | |- | ||

+ | |lyap_r || Maximal Lyapunov exponent with the Rosenstein algorithm || Does not exist || C | ||

+ | |- | ||

+ | |lyap_spec || Full spectrum of Lyapunov exponents || Does not exist || C | ||

+ | |- | ||

+ | |lzo-gm || Locally zeroth order model vs. global mean || Does not exist || C | ||

+ | |- | ||

+ | |lzo-run || Iterate a locally zeroth order model || Does not exist || C | ||

+ | |- | ||

+ | |lzo-test || Test a locally zeroth order model (old zeroth) || Does not exist || C | ||

+ | |- | ||

+ | |makenoise || Produce noise || Rand exists || Should be implemented as mfile using Octave rand functions | ||

+ | |- | ||

+ | |mem_spec || Power spectrum using the maximum entropy principle || Does not exist || C | ||

+ | |- | ||

+ | |mutual || Estimate the mutual information || Does not exist || C | ||

+ | |- | ||

+ | |notch || Notch filter || pei_tseng_notch, needs to be verified || FORTRAN | ||

+ | |- | ||

+ | |nstat_z || Nonstationarity testing via cross-prediction || Does not exist || C | ||

+ | |- | ||

+ | |pca, pc || Principle component analysis || 'pcacov' if likely the equivalent || pca - C, pc - FORTRAN | ||

+ | |- | ||

+ | |poincare || Create Poincaré sections || Does not exist || C | ||

+ | |- | ||

+ | |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 | ||

+ | |- | ||

+ | |polynom || Fit a polynomial model || same as above || same as above | ||

+ | |- | ||

+ | |polynomp || Fit a polynomial model (reads terms to fit from file) || same as above || same as above | ||

+ | |- | ||

+ | |polypar || Creates parameter file for polynomp || same as above || same as above | ||

+ | |- | ||

+ | |predict || Forecast discriminating statistics for surrogates || Does not exist || FORTRAN | ||

|- | |- | ||

− | + | |randomize || General constraint randomization (surrogates) || There are random function, but I don't think this one exists || FORTRAN | |

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− | | | + | |randomize_spikeauto_exp_random || Surrogate data preserving event time autocorrelations || Same as above || Same as above |

|- | |- | ||

− | | | + | |randomize_spikespec_exp_event || Surrogate data preserving event time power spectrum || Same as above || Same as above |

|- | |- | ||

− | | | + | |rbf || Radial basis functions fit || Does not exist || C |

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− | | | + | |recurr || Creates a recurrence plot || Does not exist || C |

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− | | | + | |resample || Resamples data || There is 'resample' in Octave, but I believe it does something else || C |

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− | | | + | |rescale || Rescale data set || This should be in Octave, cannot find... || C |

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− | | | + | |rms || Rescale data set and get mean, variance and data interval || This should be in Octave, cannot find... || FORTRNAN |

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− | | | + | |sav_gol || Savitzky-Golay filter || Does not exist || C |

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− | | | + | |spectrum || Power spectrum using FFT || bispec from tsa? || FORTRAN |

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− | | | + | |spikeauto || Autocorrelation function of event times || similar to above || FORTRAN |

|- | |- | ||

− | | | + | |spikespec || Power spectrum of event times || ar_psd, cpsd is the closest but I do not think they are the same || FORTRAN |

|- | |- | ||

− | | | + | |stp || Creates a space-time separation plot || Does not exist || FORTRAN |

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− | | | + | |surrogates || Creates surrogate data || Does not exist || FORTRAN |

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− | | | + | |timerev || Time reversal discrimating statistics for surrogates || Does not exist || FORTRAN, to be implemented as mfile |

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− | | | + | |upo || Finds unstable periodic orbits and estimates their stability || No corresponding function in Octave || FORTRAN |

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− | | | + | |upoembed || Takes the output of upo and create data files out of it || Same as above || Same as above |

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− | | | + | |wiener1, wiener2 || Wiener filter || Wiener process exists, might be similar || FORTRAN |

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− | | | + | |xc2 || Cross-correlation integral || xcorr2 || Needs to be verified that works the same way |

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− | | | + | |xcor || Cross-correlations || xcorr || Needs to be verified that works same way |

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− | | | + | |xrecur || Cross-recurrence Plot || xcorr, or xcorr2 or another function might cover this || C |

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− | + | |xzero || Locally zeroth order cross-prediction || Does not exist || C | |

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− | |xzero || Locally zeroth order cross-prediction || | ||

|} | |} |