User:Josiah425:TISEAN Package:Table of functions: Difference between revisions
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|compare || Compares two data sets || If 'rms' exists in Octave no need for port || FORTRAN | |compare || Compares two data sets || If 'rms' exists in Octave no need for port || FORTRAN | ||
|- | |- | ||
|corr || Autocorrelation function || | |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 | |d2 || Correlation dimension d2 || I believe not, don't know || c | ||
|- | |- | ||
|delay || Creates delay embedding || | |delay || Creates delay embedding || Most likely does not exist || C | ||
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|endtoend || Determine end-to-end mismatch || || | |endtoend || Determine end-to-end mismatch || || | ||
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|extrema || Determine the extrema of a time series || || | |extrema || Determine the extrema of a time series || || | ||
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|false_nearest || The false nearest neighbor algorithm || | |false_nearest || The false nearest neighbor algorithm || Does not exist || C | ||
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|ghkss || Nonlinear noise reduction || | |ghkss || Nonlinear noise reduction || There is not || C | ||
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|henon || Create a Hénon time series || | |henon || Create a Hénon time series || There is not || To m-file; already ported | ||
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|histogram || Creates histograms || || | |histogram || Creates histograms || || | ||
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|intervals || Event/intervcal conversion || || | |intervals || Event/intervcal conversion || || | ||
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|lazy || Simple nonlinear noise reduction || | |lazy || Simple nonlinear noise reduction || There is not || FORTRAN | ||
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|lfo-ar || Locally first order model vs. global AR model (old ll-ar) || || | |lfo-ar || Locally first order model vs. global AR model (old ll-ar) || || | ||
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|mem_spec || Power spectrum using the maximum entropy principle || || | |mem_spec || Power spectrum using the maximum entropy principle || || | ||
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|mutual || Estimate the mutual information || | |mutual || Estimate the mutual information || Does not exist || C | ||
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|notch || Notch filter || || | |notch || Notch filter || || | ||
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|nstat_z || Nonstationarity testing via cross-prediction || || | |nstat_z || Nonstationarity testing via cross-prediction || || | ||
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|pca || Principle component analysis || | |pca, pc || Principle component analysis || 'pcacov' if likely the equivalent || pca - C, pc - FORTRAN | ||
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|poincare || Create Poincaré sections || || | |poincare || Create Poincaré sections || || | ||
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|polypar || Creates parameter file for polynomp || || | |polypar || Creates parameter file for polynomp || || | ||
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|predict || Forecast discriminating statistics for surrogates || | |predict || Forecast discriminating statistics for surrogates || Does not exist || FORTRAN | ||
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|randomize || General constraint randomization (surrogates) || || | |randomize || General constraint randomization (surrogates) || || | ||
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|timerev || Time reversal discrimating statistics for surrogates || || | |timerev || Time reversal discrimating statistics for surrogates || || | ||
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|upo || Finds unstable periodic orbits and estimates their stability || | |upo || Finds unstable periodic orbits and estimates their stability || No corresponding function in Octave || FORTRAN | ||
|- | |- | ||
|upoembed || Takes the output of upo and create data files out of it || || | |upoembed || Takes the output of upo and create data files out of it || || |
Revision as of 00:29, 3 April 2015
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 | 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 | ||
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 | ||
events | Interval/event conversion | ||
extrema | Determine the extrema of a time series | ||
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 | ||
ikeda | Create an Ikeda time series | ||
intervals | Event/intervcal conversion | ||
lazy | Simple nonlinear noise reduction | There is not | FORTRAN |
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 | Does not exist | C |
notch | Notch filter | ||
nstat_z | Nonstationarity testing via cross-prediction | ||
pca, pc | Principle component analysis | 'pcacov' if likely the equivalent | pca - C, pc - FORTRAN |
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 | Does not exist | FORTRAN |
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 | There is 'resample' in Octave, but I believe it does something else | C |
rescale | Rescale data set | This should be in Octave, cannot find... | C |
rms | Rescale data set and get mean, variance and data interval | This should be in Octave, cannot find... | FORTRNAN |
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 | No corresponding function in Octave | FORTRAN |
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 |