| as.list.stationarity | Testing for stationarity in a time series |
| as.matrix.embedSeries | Creates a delay embedding of a single variable time series |
| as.matrix.spaceTime | Space time separation plot |
| beamchaos | Chaotic beam data |
| chaoticInvariant | Class for chaotic invariant objects |
| corrDim | Correlation dimension |
| determinism | Detecting determinism in a time series |
| DFA | Detrended fluctuation analysis |
| dispersion | Dispersion analysis |
| ecgrr | Electrocardiogram R-R Interval Data |
| eda.plot | Generic function for generating extended data analysis plots |
| eda.plot.chaoticInvariant | Class for chaotic invariant objects |
| eda.plot.determinism | Detecting determinism in a time series |
| eda.plot.embedSeries | Creates a delay embedding of a single variable time series |
| eda.plot.fractalBlock | Class constructor for block-dependent estimators for stochastic fractal time series |
| eda.plot.KDE | Nonparametric multidimensional probability density function estimation |
| eda.plot.spaceTime | Space time separation plot |
| eda.plot.surrogate | Surrogate data generation |
| eegduke | Electroencephalogram Recordings of a Seizure |
| embedSeries | Creates a delay embedding of a single variable time series |
| FDSimulate | Simulation of an FD process with time varying model parameters |
| FDWhittle | Estimate the Hurst coefficient by Whittle's method |
| findNeighbors | Nearest neighbor search in a multidimensional space |
| FNN | Estimation of the proper embedding dimension for a single-variable time series |
| FNS | Estimation of the proper embedding dimension for a single-variable time series |
| fractalBlock | Class constructor for block-dependent estimators for stochastic fractal time series |
| HDEst | Hurvich-Deo estimate of number of frequencies to use in a periodogram regression |
| henon | Henon map |
| hurstACVF | Estimate the Hurst coefficient by regression of scaled asinh plot of ACVF vs log(lag) |
| hurstBlock | Hurst coefficient estimation in the time domain |
| hurstSpec | Hurst coefficient estimation via spectral regression |
| infoDim | Information dimension |
| KDE | Nonparametric multidimensional probability density function estimation |
| lmACF | ACF, PACF, and ACVF for various stochastic fractal time series models |
| lmConfidence | Confidence intervals for unknown mean |
| lmConvert | Stochastic fractal exponent conversion |
| lmModel | Constructor function for objects of class "lmModel" |
| lmSDF | SDF for various stochastic fractal time series models |
| lmSimulate | Stochastic fractal time series simulation |
| localProjection | Time series denoising via a local projection filtering technique |
| lorenz | Chaotic response of the Lorenz system |
| lorenz.ode | Lorenz system ODEs |
| lyapunov | Local-Global Lyapunov Spectrum Estimation |
| medianFilter | Median filtering of a time series |
| pd5si | Gait stride intervals for a patient with Parkinson's Disease |
| plot.chaoticInvariant | Class for chaotic invariant objects |
| plot.determinism | Detecting determinism in a time series |
| plot.embedSeries | Creates a delay embedding of a single variable time series |
| plot.FDSimulate | Simulation of an FD process with time varying model parameters |
| plot.FNN | Estimation of the proper embedding dimension for a single-variable time series |
| plot.fractalBlock | Class constructor for block-dependent estimators for stochastic fractal time series |
| plot.KDE | Nonparametric multidimensional probability density function estimation |
| plot.lyapunov | Local-Global Lyapunov Spectrum Estimation |
| plot.spaceTime | Space time separation plot |
| plot.surrogate | Surrogate data generation |
| poincareMap | Create a Poincare map |
| print.chaoticInvariant | Class for chaotic invariant objects |
| print.determinism | Detecting determinism in a time series |
| print.embedSeries | Creates a delay embedding of a single variable time series |
| print.FDSimulate | Simulation of an FD process with time varying model parameters |
| print.FNN | Estimation of the proper embedding dimension for a single-variable time series |
| print.fractalBlock | Class constructor for block-dependent estimators for stochastic fractal time series |
| print.KDE | Nonparametric multidimensional probability density function estimation |
| print.lyapunov | Local-Global Lyapunov Spectrum Estimation |
| print.spaceTime | Space time separation plot |
| print.stationarity | Testing for stationarity in a time series |
| print.summary.chaoticInvariant | Class for chaotic invariant objects |
| print.summary.lyapunov | Local-Global Lyapunov Spectrum Estimation |
| print.summary.stationarity | Testing for stationarity in a time series |
| print.surrogate | Surrogate data generation |
| RoverS | Estimate the Hurst coefficient by rescaled range (R/S) method |
| spaceTime | Space time separation plot |
| stationarity | Testing for stationarity in a time series |
| summary.determinism | Detecting determinism in a time series |
| summary.lyapunov | Local-Global Lyapunov Spectrum Estimation |
| summary.stationarity | Testing for stationarity in a time series |
| surrogate | Surrogate data generation |
| timeLag | Estimate the proper time lag for single variable delay embeddings |
| [.embedSeries | Creates a delay embedding of a single variable time series |