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<html><head><title>Nonlinear Time Series Routines</title></head><body bgcolor="#ffffff"><h1 align=center><a name="top">TISEAN 3.0.1<br>All programs in alphabetical order</h1><table align=center border><tr><td><a href="docs_c/arima-model.html">arima-model</a></td><td>Fit and possibly iterate an ARIMA model</td><tr><td><a href="docs_c/ar-model.html">ar-model</a></td><td>Fit and possibly iterate an Autoregessive model</td></tr><tr><td><a href="docs_f/ar-run.html">ar-run</a></td><td>Iterate an Autoregessive model</td></tr><tr><td><a href="docs_c/av-d2.html">av-d2</a></td><td>Simply smooth output of <a href="docs_c/d2.html">d2</a></td></tr><tr><td><a href="docs_c/boxcount.html">boxcount</a></td><td>Renyi Entopies of Qth order</td></tr><tr><td><a href="docs_f/c1.html">c1</a></td><td>Fixed mass estimation of D1</td></tr><tr><td><a href="docs_f/c2d.html">c2d</a></td><td>Get local slopes from correlation integral</td></tr><tr><td><a href="docs_f/c2g.html">c2g</a></td><td>Gaussian kernel of C2</td></tr><tr><td><a href="docs_f/c2t.html">c2t</a></td><td>Takens estimator of D2</td></tr><tr><td><a href="docs_f/choose.html">choose</a></td><td>Choose rows and/or columns from a data file</td></tr><tr><td><a href="docs_f/compare.html">compare</a></td><td>Compares two data sets</td></tr><tr><td><a href="docs_c/corr.html">corr</a></td><td>Autocorrelation function</td></tr><tr><td><a href="docs_c/d2.html">d2</a></td><td>Correlation dimension d2</td></tr><tr><td><a href="docs_c/delay.html">delay</a></td><td>Creates delay embedding</td></tr><tr><td><a href="docs_f/endtoend.html">endtoend</a></td><td>Determine end-to-end mismatch</td></tr><tr><td><a href="docs_f/events.html">events</a></td><td>Interval/event conversion</td></tr><tr><td><a href="docs_c/extrema.html">extrema</a></td><td>Determine the extrema of a time series</td></tr><tr><td><a href="docs_c/false_nearest.html">false_nearest</a></td><td>The false nearest neighbor algorithm</td></tr><tr><td><a href="docs_c/ghkss.html">ghkss</a></td><td>Nonlinear noise reduction</td></tr><tr><td><a href="docs_f/henon.html">henon</a></td><td>Create a Hénon time series</td></tr><tr><td><a href="docs_c/histogram.html">histogram</a></td><td>Creates histograms</td></tr><tr><td><a href="docs_f/ikeda.html">ikeda</a></td><td>Create an Ikeda time series</td></tr><tr><td><a href="docs_f/intervals.html">intervals</a></td><td>Event/intervcal conversion</td></tr><tr><td><a href="docs_f/lazy.html">lazy</a></td><td>Simple nonlinear noise reduction</td></tr><tr><td><a href="docs_c/lfo-ar.html">lfo-ar</a></td><td>Locally first order model vs. global AR model(old <font color=red>ll-ar</font>)</td></tr><tr><td><a href="docs_c/lfo-run.html">lfo-run</a></td><td>Iterate a locally first order model (old <font color=red>nstep</font>)</td></tr><tr><td><a href="docs_c/lfo-test.html">lfo-test</a></td><td>Test a locally first order model (old <font color=red>onestep</font>)</td></tr><tr><td><a href="docs_f/lorenz.html">lorenz</a></td><td>Create a Lorenz time series</td></tr><tr><td><a href="docs_c/low121.html">low121</a></td><td>Time domain low pass filter</td></tr><tr><td><a href="docs_c/lyap_k.html">lyap_k</a></td><td>Maximal Lyapunov exponent with the Kantz algorithm</td></tr><tr><td><a href="docs_c/lyap_r.html">lyap_r</a></td><td>Maximal Lyapunov exponent with the Rosenstein algorithm</td></tr><tr><td><a href="docs_c/lyap_spec.html">lyap_spec</a></td><td>Full spectrum of Lyapunov exponents</td></tr><tr><td><a href="docs_c/lzo-gm.html">lzo-gm</a></td><td>Locally zeroth order model vs. global mean</td></tr><tr><td><a href="docs_c/lzo-run.html">lzo-run</a></td><td>Iterate a locally zeroth order model</td></tr><tr><td><a href="docs_c/lzo-test.html">lzo-test</a></td><td>Test a locally zeroth order model (old <font color=red>zeroth</font>)</td></tr><tr><td><a href="docs_c/makenoise.html">makenoise</a></td><td>Produce noise</td></tr><tr><td><a href="docs_c/mem_spec.html">mem_spec</a></td><td>Power spectrum using the maximum entropy principle</td></tr><tr><td><a href="docs_c/mutual.html">mutual</a></td><td>Estimate the mutual information</td></tr><tr><td><a href="docs_f/notch.html">notch</a></td><td>Notch filter</td></tr><tr><td><a href="docs_c/nstat_z.html">nstat_z</a></td><td>Nonstationarity testing via cross-prediction</td></tr><tr><td><a href="docs_c/pca.html">pca</a></td><td>Principle component analysis</td></tr><tr><td><a href="docs_c/poincare.html">poincare</a></td><td>Create Poincaré sections</td></tr><tr><td><a href="docs_c/polyback.html">polyback</a></td><td>Fit a polynomial model (backward elimination)</td></tr><tr><td><a href="docs_c/polynom.html">polynom</a></td><td>Fit a polynomial model</td></tr><tr><td><a href="docs_c/polynomp.html">polynomp</a></td><td>Fit a polynomial model (reads terms to fit from file)</td></tr><tr><td><a href="docs_c/polypar.html">polypar</a></td><td>Creates parameter file for <ahref="docs_c/polynomp.html">polynomp</a></td> </tr><tr><td><a href="docs_f/predict.html">predict</a></td><td>Forecast discriminating statistics for surrogates</td></tr><tr><td><a href="docs_f/randomize.html">randomize</a></td><td>General constraint randomization (surrogates)</td></tr><tr><td><a href="docs_f/randomize_spikeauto_exp_random.html">randomize_spikeauto_exp_random</a></td><td>Surrogate data preserving event time autocorrelations</td></tr><tr><td><a href="docs_f/randomize_spikespec_exp_event.html">randomize_spikespec_exp_event</a></td><td>Surrogate data preserving event time power spectrum</td></tr><tr><td><a href="docs_c/rbf.html">rbf</a></td><td>Radial basis functions fit</td></tr><tr><td><a href="docs_c/recurr.html">recurr</a></td><td>Creates a recurrence plot</td></tr><tr><td><a href="docs_c/resample.html">resample</a></td><td>Resamples data</td></tr><tr><td><a href="docs_c/rescale.html">rescale</a></td><td>Rescale data set</td></tr><tr><td><a href="docs_f/rms.html">rms</a></td><td>Rescale data set and get mean, variance and data interval</td></tr><tr><td><a href="docs_c/sav_gol.html">sav_gol</a></td><td>Savitzky-Golay filter</td></tr><tr><td><a href="docs_f/spectrum.html">spectrum</a></td><td>Power spectrum using FFT</td></tr><tr><td><a href="docs_f/spikeauto.html">spikeauto</a></td><td>Autocorrelation function of event times</td></tr><tr><td><a href="docs_f/spikespec.html">spikespec</a></td><td>Power spectrum of event times</td></tr><tr><td><a href="docs_f/stp.html">stp</a></td><td>Creates a space-time separation plot</td></tr><tr><td><a href="docs_f/surrogates.html">surrogates</a></td><td>Creates surrogate data</td></tr><tr><td><a href="docs_f/timerev.html">timerev</a></td><td>Time reversal discrimating statistics for surrogates</td></tr><tr><td><a href="docs_f/upo.html">upo</a></td><td>Finds unstable periodic orbits and estimates their stability</td></tr><tr><td><a href="docs_f/upoembed.html">upoembed</a></td><td>Takes the output of <a href="docs_f/upo.html">upo</a> and createdata files out of it</td></tr><tr><td><a href="docs_f/wiener.html">wiener</a></td><td>Wiener filter</td></tr><tr><td><a href="docs_f/xc2.html">xc2</a></td><td>Cross-correlation integral</td></tr><tr><td><a href="docs_c/xcor.html">xcor</a></td><td>Cross-correlations</td></tr><tr><td><a href="docs_f/xrecur.html">xrecur</a></td><td>Cross-recurrence Plot</td></tr><tr><td><a href="docs_c/xzero.html">xzero</a></td><td>Locally zeroth order cross-prediction</td></tr></table><hr><em>Copyright © (1998-2007) Rainer Hegger, Holger Kantz, ThomasSchreiber</em> <br><p><a href="../index.html" target="_top">TISEAN home</a></p></body></html>⌨️ 快捷键说明
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