# Difference between revisions of "User:Josiah425:TISEAN Package:Table of functions"

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

|- | |- | ||

− | |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) || Does not exist || C |

|- | |- | ||

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

|- | |- | ||

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

|- | |- | ||

|lorenz || Create a Lorenz time series || || | |lorenz || Create a Lorenz time series || || | ||

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|low121 || Time domain low pass filter || || | |low121 || Time domain low pass filter || || | ||

|- | |- | ||

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

|- | |- | ||

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

|- | |- | ||

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

|- | |- | ||

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

|- | |- | ||

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

|- | |- | ||

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

|- | |- | ||

|makenoise || Produce noise || || | |makenoise || Produce noise || || | ||

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|poincare || Create Poincaré sections || || | |poincare || Create Poincaré sections || || | ||

|- | |- | ||

− | |polyback || Fit a polynomial model (backward elimination) || | + | |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 || | + | |polynom || Fit a polynomial model || same as above || same as above |

|- | |- | ||

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

|- | |- | ||

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

|- | |- | ||

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

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|randomize_spikespec_exp_event || Surrogate data preserving event time power spectrum || || | |randomize_spikespec_exp_event || Surrogate data preserving event time power spectrum || || | ||

|- | |- | ||

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

|- | |- | ||

|recurr || Creates a recurrence plot || || | |recurr || Creates a recurrence plot || || | ||

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|xrecur || Cross-recurrence Plot || || | |xrecur || Cross-recurrence Plot || || | ||

|- | |- | ||

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

|} | |} |

## Revision as of 18:02, 2 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) | 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 | ||

low121 | Time domain low pass filter | ||

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) | Doest not exist | C |

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) | 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) | ||

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 | Does not exist | C |

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 | Does not exist | C |