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~~! Program Name !! Program Description !! Corresponding Octave Function !! Comments~~~~|-~~~~| arima-model || Fit and possibly iterate an ARIMA model |~~| ~~generalizes TSA arma functions || This is a c-file ~~No color means that ~~can be wrapped in C++/mfile/octfile code~~~~|-~~~~|ar-model || Fit and possibly iterate an Autoregessive model || 'aar' in TSA || 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 || Can be implemented with filter in core || C~~~~|-~~~~|boxcount || Renyi Entopies of Qth order || None in GNU Octave (maybe in info-theory but it is not worth the pain) || C~~~~|-~~~~|c1 || Fixed mass estimation of D1 || None in GNU Octave || FORTRAN~~~~|-~~~~|c2d || Get local slopes from correlation integral || None in GNU Octave || FORTRAN~~~~|-~~~~|c2g || Gaussian kernel of C2 || None in GNU Octave || FORTRAN~~~~|-~~~~|c2t || Takens estimator of D2 || None in GNU Octave || FORTRAN~~~~|-~~~~|choose || Choose rows and/or columns from a data file || Does not need to be ported || ------~~~~|-~~~~|compare || Compares two data sets || Does not need to be ported || FORTRAN~~~~|-~~~~|corr, autocorr || Autocorrelation ~~nothing about this function ~~|| xcorr in signal || corr -C, autocorr (faster according to documentation) - FORTRAN~~~~|-~~~~|d2 || Correlation dimension d2 || None in GNU Octave || c~~~~|-~~~~|delay || Creates delay embedding || None in GNU Octave (easy to implement in Octave but not worth the effort) || C~~~~|-~~~~|endtoend || Determine end-to-end mismatch || None in GNU Octave || FORTRAN~~~~|-~~~~|events || Interval/event conversion || None in GNU Octave || FORTRAN to be implemented as mfile~~~~|-~~~~|extrema || Determine the extrema of a time series || findpeaks in signal (but maybe is just easier to port) || C~~~~|-~~~~|false_nearest || The false nearest neighbor algorithm || None in GNU Octave || C~~~~|-~~~~|ghkss || Nonlinear noise reduction || None in GNU Octave || C~~~~|-~~~~|henon || Create a Hénon time series || There is not || To m-file; already ported~~~~|-~~~~|histogram || Creates histograms || hist in core || C ~~~~|-~~~~|ikeda || Create an Ikeda time series || None in GNU Octave || 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 || None in GNU Octave || FORTRAN~~~~|-~~~~|lfo-ar || Locally first order model vs. global AR model (old ll-ar) || None in GNU Octave || C~~has been determined|~~-~~}~~|lfo-run || Iterate a locally first order model (old nstep) || None in GNU Octave || C~~~~|-~~{|~~lfo-test || Test a locally first order model (old onestep) || None in GNU Octave || C~~~~|-~~~~|lorenz || Create a Lorenz time series || None in GNU Octave || 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 || None in GNU Octave || C~~~~|-~~~~|lyap_r || Maximal Lyapunov exponent with the Rosenstein algorithm || None in GNU Octave || C~~~~|-~~~~|lyap_spec || Full spectrum of Lyapunov exponents || None in GNU Octave || C~~~~|-~~~~|lzo-gm || Locally zeroth order model vs. global mean || None in GNU Octave || C~~~~|-~~~~|lzo-run || Iterate a locally zeroth order model || None in GNU Octave || C~~~~|-~~~~|lzo-test || Test a locally zeroth order model (old zeroth) || None in GNU Octave || C~~~~|-~~~~|makenoise || Produce noise || Rand exists || Should be implemented as mfile using Octave rand functions~~~~|-~~~~|mem_spec || Power spectrum using the maximum entropy principle || None in GNU Octave || C~~~~|-~~~~|mutual || Estimate the mutual information || None in GNU Octave || C~~~~|-~~~~|notch || Notch filter || pei_tseng_notch, needs to be verified || FORTRAN~~~~|-~~~~|nstat_z || Nonstationarity testing via cross-prediction || None in GNU Octave || C~~~~|-~~~~|pca, pc || Principle component analysis || 'pcacov' if likely the equivalent || pca - C, pc - FORTRAN~~~~|-~~~~|poincare || Create Poincaré sections || None in GNU Octave || 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 || None in GNU Octave || FORTRAN~~class="wikitable"
~~|randomize || General constraint randomization (surrogates) || There are random function, but I don't think this one exists || FORTRAN~~! Program Name !! Program Description !! Corresponding Octave Function !! Lanuguage of Origin !! How to port !! Status

added legend

The choice whether a program exist in Octave is based only on comparing package/octave documentation with the TISEAN documentation. As of now I have not compared any code, nor checked if any sample data gives the same results from both functions (the octave ones and the TISEAN ones).

The legend to understand the table is as follows:

{| class="wikitable"

|-style="background: LightGreen"

|Green means the function is ported, tested or is not needed

|-style="background: LightSalmon"

|Red means the function was thought to have been similar but isn't

|-style="background: Yellow"

|Yellow means that the correlation between the TISEAN and Octave function needs to be verified

|-

|-

|-

|~~randomize_spikeauto_exp_random ~~arima-model || ~~Surrogate data preserving event time autocorrelations ~~Fit and possibly iterate an ARIMA model || ~~Same as above ~~generalizes TSA arma functions || C || wrapped in C++/mfile/octfile code || ~~Same as above~~

|-

|~~randomize_spikespec_exp_event ~~ar-model || ~~Surrogate data preserving event time power spectrum ~~Fit and possibly iterate an Autoregessive model || ~~Same as above ~~'aar' in TSA; see also: aarmam, adim, amarma, mvaar from TSA || C || wrapped in C++/mfile/octfile code || ~~Same as above~~

|-

|~~rbf ~~ar-run || ~~Radial basis functions fit ~~Iterate an Autoregessive model || Same as above || FORTRAN || wrapped in C++/mfile/octfile code |||-style="background: LightGreen"|av-d2 || Simply smooth output of d2 || Can be implemented with filter in core || C || |||-style="background: LightGreen"|boxcount || Renyi Entopies of Qth order || None in GNU Octave (maybe in info-theory but it is not worth the pain) || C || wrapped in C++/mfile/octfile code |||-style="background: LightGreen"|c1 || Fixed mass estimation of D1 || None in GNU Octave || FORTRAN || wrapped in C++/mfile/octfile code |||-style="background: LightGreen"|c2d || Get local slopes from correlation integral || None in GNU Octave || FORTRAN || wrapped in C++/mfile/octfile code |||-style="background: LightGreen"|c2g || Gaussian kernel of C2 || None in GNU Octave || FORTRAN || wrapped in C++/mfile/octfile code |||-style="background: LightGreen"|c2t || Takens estimator of D2 || None in GNU Octave || FORTRAN || wrapped in C++/mfile/octfile code |||-style="background: LightGreen"|choose || Choose rows and/or columns from a data file || Does not need to be ported || FORTRAN || ----- || Not Needed|-style="background: LightGreen"|compare || Compares two data sets || Does not need to be ported || FORTRAN || ------ || Not Needed|-style="background: LightGreen"|corr, autocorr || Autocorrelation function || xcorr in signal || corr -C, autocorr (faster according to documentation) - FORTRAN || ------- || Different usage, same result|-style="background: LightGreen"|d2 || Correlation dimension d2 || None in GNU Octave || C || wrapped in C++/mfile/octfile code |||-style="background: LightGreen"|delay || Creates delay embedding || None in GNU Octave (easy to implement in Octave but not worth the effort) || C || wrapped in C++/mfile/octfile code || Ported&Tested|-style="background: LightGreen"|endtoend || Determine end-to-end mismatch || None in GNU Octave || FORTRAN || wrapped in C++/mfile/octfile code || Ported&Tested

|-

|~~recurr ~~events || ~~Creates ~~Interval/event conversion || None in GNU Octave || FORTRAN || To be reimplemented as m-file |||-style="background: LightSalmon"|extrema || Determine the extrema of a time series || findpeaks in signal is *not* the same || C || |||-style="background: LightGreen"|false_nearest || The false nearest neighbor algorithm || None in GNU Octave || C || wrapped in C++/mfile/octfile code || Ported&Tested|-style="background: LightGreen"|ghkss || Nonlinear noise reduction || None in GNU Octave || C || wrapped in C++/mfile/octfile code || Ported&Tested|-style="background: LightGreen"|henon || Create a ~~recurrence plot ~~Hénon time series || None in GNU Octave || FORTRAN || To be reimplemented as m-file || Ported&Checked|-style="background: LightGreen"|histogram || Creates histograms || hist in core || C || || Different usage, same result|-style="background: LightGreen"|ikeda || Create an Ikeda time series || None in GNU Octave || FORTRAN || To be reimplemented as mfile || Ported&Tested

|-

|~~resample ~~intervals || ~~Resamples data ~~Event/intervcal conversion || ~~There is 'resample' ~~Might exist under different name || FORTRAN || To be reimplemented as mfile |||-style="background: LightGreen"|lazy || Simple nonlinear noise reduction || None in GNU Octave || FORTRAN || wrapped in C++/mfile/octfile code || Ported&Tested|-style="background: LightGreen"|lfo-ar || Locally first order model vs. global AR model (old ll-ar) || None in GNU Octave || C || wrapped in C++/mfile/octfile code |||-style="background: LightGreen"|lfo-run || Iterate a locally first order model (old nstep) || None in GNU Octave~~, but I believe it does something else ~~|| C|| wrapped in C++/mfile/octfile code |||-style="background: LightGreen"|lfo-test || Test a locally first order model (old onestep) || None in GNU Octave || C || wrapped in C++/mfile/octfile code |||-style="background: Yellow"|lorenz || Create a Lorenz time series || Can be implemented in GNU Octave using lsode or odepkg|| FORTRAN || mfile ||

|-

|~~rescale ~~low121 || ~~Rescale data set ~~Time domain low pass filter || ~~This should be ~~There are lowpass filters in Octave: buttap, ~~cannot find..~~cheb1ap, cheb2ap, ellipap, sftrans, but I don't think they perform this task || C || Reimplement as mfile |||-style="background: LightGreen"|lyap_k || Maximal Lyapunov exponent with the Kantz algorithm || None in GNU Octave || C || wrapped in C++/mfile/octfile code |||-style="background: LightGreen"|lyap_r || Maximal Lyapunov exponent with the Rosenstein algorithm || None in GNU Octave || C || wrapped in C++/mfile/octfile code |||-style="background: LightGreen"|lyap_spec || Full spectrum of Lyapunov exponents || None in GNU Octave || C || wrapped in C++/mfile/octfile code |||-style="background: LightGreen"|lzo-gm || Locally zeroth order model vs. global mean || None in GNU Octave || C || wrapped in C++/mfile/octfile code || Ported&Tested|-style="background: LightGreen"|lzo-run || Iterate a locally zeroth order model || None in GNU Octave || C || wrapped in C++/mfile/octfile code || Ported&Tested|-style="background: LightGreen"|lzo-test || Test a locally zeroth order model (old zeroth) || None in GNU Octave || C || wrapped in C++/mfile/octfile code || Ported&Tested

|-

|~~rms ~~makenoise || ~~Rescale data set and get mean, variance and data interval ~~Produce noise || ~~This should ~~Rand exists || Should be implemented as mfile using Octave rand functions || wrapped in ~~Octave, cannot find... ~~C++/mfile/octfile code || ~~FORTRNAN~~

|-

|~~sav_gol ~~mem_spec || ~~Savitzky~~Power spectrum using the maximum entropy principle || None in GNU Octave || C || wrapped in C++/mfile/octfile code |||-~~Golay ~~style="background: LightGreen"|mutual || Estimate the mutual information || None in GNU Octave || C || wrapped in C++/mfile/octfile code || Ported&Tested|-style="background: Yellow"|notch || Notch filter || ~~sgolayfilt ~~pei_tseng_notch, needs to be verified || FORTRAN || wrapped in ~~signal ~~C++/mfile/octfile code || ~~C~~

|-

|~~spectrum ~~nstat_z || ~~Power spectrum using FFT ~~Nonstationarity testing via cross-prediction || ~~bispec ~~None in GNU Octave || C ||wrapped in C++/mfile/octfile code |||-style="background: LightGreen"|pca, pc || Principle component analysis || 'pcacov' if likely the equivalent; pricomp in statistics || pca - C, pc - FORTRAN || wrapped in C++/mfile/octfile code || Ported&Tested|-style="background: LightGreen"|poincare || Create Poincaré sections || None in GNU Octave || C || wrapped in C++/mfile/octfile code || Ported&Tested|-style="background: LightSalmon"|polyback || Fit a polynomial model (backward elimination) || polyfit, detrend, wpolyfit are not similar || C || wrapped in C++ || Porting needed|-style="background: LightGreen"|polynom || Fit a polynomial model || same as above || C || |||-style="background: LightSalmon"|polynomp || Fit a polynomial model (reads terms to fit from ~~tsa? ~~file) || same as above || C || |||-style="background: LightSalmon"|polypar || Creates parameter file for polynomp || same as above || C || |||-style="background: LightGreen"|predict || Forecast discriminating statistics for surrogates || None in GNU Octave || FORTRAN|| wrapped in C++/mfile/octfile code || Same as lzo_test; Not Needed

|-

|~~spikeauto ~~randomize || ~~Autocorrelation ~~General constraint randomization (surrogates) || There are random function ~~of event times ~~, but I don't think this one exists || FORTRAN || ~~similar to above ~~wrapped in C++/mfile/octfile code || ~~FORTRAN~~

|-

|~~spikespec ~~randomize_spikeauto_exp_random || ~~Power spectrum of ~~Surrogate data preserving event ~~times ~~time autocorrelations || ~~ar_psd, cpsd is the closest but I do not think they are the same ~~Same as above || FORTRAN|| wrapped in C++/mfile/octfile code ||

|-

|~~stp ~~randomize_spikespec_exp_event || ~~Creates a space~~Surrogate data preserving event time power spectrum || Same as above || FORTRAN || wrapped in C++/mfile/octfile code |||-~~time separation plot ~~style="background: LightGreen"|rbf || Radial basis functions fit || None in GNU Octave || ~~FORTRAN~~C || wrapped in C++/mfile/octfile code ||

|-

|~~surrogates ~~recurr || Creates ~~surrogate data ~~a recurrence plot || None in GNU Octave || ~~FORTRAN~~C || wrapped in C++/mfile/octfile code ||

|-

|~~timerev ~~resample || ~~Time reversal discrimating statistics for surrogates ~~Resamples data || ~~None ~~There is 'resample' in ~~GNU ~~Octave , but I believe it does something else || C || ~~FORTRAN, to be implemented as ~~wrapped in C++/mfile/octfile code ||

|-

|~~upo ~~rescale || ~~Finds unstable periodic orbits ~~Rescale data set || This should be in Octave, cannot find... || C || wrapped in C++/mfile/octfile code |||-style="background: LightGreen"|rms || Rescale data set and get mean, variance and ~~estimates their stability ~~data interval || ~~No corresponding function ~~This should be in Octave , cannot find... || FORTRNAN || wrapped in C++/mfile/octfile code || Not Needed|-style="background: Yellow"|sav_gol || Savitzky-Golay filter || sgolayfilt in signal || C || |||-style="background: LightGreen"|spectrum || Power spectrum using FFT || abs (fft (;)) || FORTRAN|| Rewrite as m-file || Ported&Tested

|-

|~~upoembed ~~spikeauto || ~~Takes the output ~~Autocorrelation function of ~~upo and create data files out of it ~~event times || ~~Same as ~~similar to above || ~~Same as above~~FORTRAN || ||

|-

|~~wiener1, wiener2 ~~spikespec || ~~Wiener filter ~~Power spectrum of event times || ~~Wiener process exists~~ar_psd, ~~might be similar ~~cpsd is the closest but I do not think they are the same || FORTRAN|| ||

|-

|~~xc2 ~~stp || ~~Cross~~Creates a space-~~correlation integral ~~time separation plot || ~~xcorr2 ~~None in GNU Octave || ~~Needs to ~~FORTRAN || wrapped in C++/mfile/octfile code |||-style="background: LightGreen"|surrogates || Creates surrogate data || None in GNU Octave || FORTRAN || wrapped in C++/mfile/octfile code || Ported&Tested|-style="background: LightGreen"|timerev || Time reversal discrimating statistics for surrogates || None in GNU Octave || FORTRAN || To be ~~verified that works ~~reimplemented as mfile || Ported&Tested|-style="background: LightGreen"|upo || Finds unstable periodic orbits and estimates their stability || None in GNU Octave || FORTRAN || wrapped in C++/mfile/octfile code || Ported&Tested|-style="background: LightGreen"|upoembed || Takes the ~~same way~~output of upo and create data files out of it || None in GNU Octave || FORTAN || wrapped in C++/mfile/octfile code || Ported&Tested

|-

|~~xcor ~~wiener1, wiener2 || ~~Cross-correlations ~~Wiener filter || ~~xcorr ~~Wiener process exists, might be similar || FORTRAN || wrapped in C++/mfile/octfile code || ~~Needs to be verified that works same way~~

|-

|~~xrecur ~~xc2 || Cross-~~recurrence Plot ~~correlation integral || xcorr2 - Needs to be verified that works the same way || FORTRAN || wrapped in C++/mfile/octfile code |||-style="background: Yellow"|xcor || Cross-correlations || xcorr~~, or xcorr2 or another function might cover this ~~- Needs to be verified that works same way || C|| wrapped in C++/mfile/octfile code ||

|-

|xrecur || Cross-recurrence Plot || xcorr, or xcorr2 or another function might cover this || C || wrapped in C++/mfile/octfile code |||-style="background: LightGreen"|xzero || Locally zeroth order cross-prediction || None in GNU Octave || C|| wrapped in C++/mfile/octfile code ||

|}

156

edits

Retrieved from "https://wiki.octave.org/Special:MobileDiff/6072...6545"

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