Man pages for FredHasselman/casnet
A Toolbox for Studying Complex Adaptive Systems and Networks
| ac_win | Windowed autocorrelation function |
| add_alpha | Add transparency to a colour |
| aggregate_bins | aggregate_bins |
| as.numeric_character | Character vector to named numeric vector |
| as.numeric_discrete | Discrete (factor or character) to numeric vector |
| as.numeric_factor | Numeric factor to numeric vector |
| bandReplace | Replace matrix diagonals |
| casnet-deprecated | Deprecated functions in package casnet. |
| casnet-package | casnet: A Toolbox for Studying Complex Adaptive Systems and... |
| checkPkg | Check package |
| ColouredNoise | Coloured noise data |
| createCorridor | Corridor analysis |
| dc_ccp | Cumulative Complexity Peaks (CCP) |
| DC_D | Distribution Uniformity |
| DC_F | Fluctuation Intensity |
| dc_win | Dynamic Complexity |
| eig_win | Windowed Eigenvalue (PCA) |
| elascer | Elastic Scaler - A Flexible Rescale Function |
| est_emDim | Estimate number of embedding dimensions |
| est_emLag | Estimate embedding lag (tau) |
| est_parameters | Estimate RQA parameters |
| est_parameters_roc | Estimate ROC radius |
| est_radius | Estimate Radius. |
| est_radius_rqa | Estimate Radius without building a recurrence matrix |
| fd_allan | Allan Variance Analysis |
| fd_boxcount2D | 2D Boxcount for 1D signal |
| fd_dfa | Detrended Fluctuation Analysis (DFA) |
| fd_mfdfa | Multi-fractal Detrended Fluctuation Analysis |
| fd_prepSeries | Prepare time series for fluctuation analysis |
| fd_psd | Power Spectral Density Slope (PSD). |
| fd_RR | Relative Roughness |
| fd_sda | Standardised Dispersion Analysis (SDA). |
| fd_sev | Calculate FD using Sevcik's method |
| flight_Cauchy | Create Cauchy Flight |
| flight_LevyPareto | Create a Levy-Pareto flight |
| flight_Rayleigh | Create Rayleigh Flight (Brownian Motion) |
| fltrIT | Wrapper for filtfilt |
| fnn | False Nearest Neighbours |
| getColours | Get some nice colours |
| get_fluct | Get fluctuations (internal) |
| get_os | Which OS is running? |
| getPairs | Get all combinations |
| growth_ac | Examples of dynamical growth models (maps) |
| growth_ac_cond | Examples of conditional dynamical growth models (maps) |
| Heaviside | Heaviside step function |
| HurvichDeo | HurvichDeo |
| inf_MSE | Multi-Scale Entropy |
| inf_SampEn | Sample Entropy |
| is.date | It's a Date! |
| layout_as_spiral | Layout a graph on a spiral |
| lv_Ndim | Lotka-Volterra model for N species |
| make_spiral_graph | Make Spiral Graph |
| manyAnalystsESM | Data from the Many Analysts study. |
| mat_coursegrain | Course grain a matrix for plotting |
| mat_di2bi | Distance to binary matrix |
| mat_di2ch | Distance to chromatic matrix |
| mat_di2we | Distance to weighted matrix |
| mat_hamming | Calculate Hamming distance |
| mat_ind | Get indices of matrix diagonals, rows, or columns |
| mat_mat2ind | Matrix to indexed data frame |
| mat_we2bi | Weighted to Binary matrix |
| mif | Mutual Information Function |
| mi_interlayer | Inter-layer mutual information |
| mi_mat | Mutual Information variations |
| monoH | mono Hurst |
| mrn | Multiplex Recurrence Network |
| mrn_plot | Multiplex Recurrence Network Plot |
| noise_fBm | Generate fractional Brownian motion |
| noise_fGn | Generate fractional Gaussian noise |
| noise_powerlaw | Generate noise series with power law scaling exponent |
| pacf_fisherZ | FisherZ for PACF |
| plotDC_ccp | Plot Cumulative Complexity Peaks |
| plotDC_helper | Create breaks for Resonance plots |
| plotDC_lvl | Plot Peaks versus Levels |
| plotDC_res | Plot Complexity Resonance Diagram |
| plotFD_loglog | Plot output from fluctuation analyses based on log-log... |
| plotMRN_win | Plot windowed Multiplex Recurrence Network measures |
| plotNET_BA | Example of Barabasi scale-free network |
| plotNET_groupColour | Vertex and Edge Group Colours |
| plotNET_groupWeight | Set Edge weights by group |
| plotNET_prep | Plot Network Based on RQA |
| plotNET_SW | Example of Strogatz-Watts small-world network |
| plotRED_acf | Plot ACF and PACF |
| plotRED_mif | Plot various MI functions |
| plotRN_phaseDensity | Phase Density for each dimension |
| plotRN_phaseProfile | Profile Plot |
| plotRN_phaseSeries | Phase Series plot |
| plotSUR_hist | Surrogate Test |
| plotTS_multi | Plot Multivariate Time Series Data |
| repmat | Repeat Copies of a Matrix |
| return_error | Return Error |
| rn | Create a Recurrence Network Matrix |
| RNG | Random Number Sequences |
| rn_measures | Recurrence Network Measures |
| rn_phases | Extract Phases from weighted RN |
| rn_plot | Plot (thresholded) distance matrix as a network |
| rn_recSpec | Recurrence Time Spectrum |
| rn_strengthDist | Strength versus Degree scaling relation |
| rn_transition | Create transition network |
| rp | Create a Distance Matrix |
| rp_calc | rp_calc |
| rp_checkfix | Check a Recurrence Matrix |
| rp_cl | Fast (C)RQA (command line crp) |
| rp_cl_main | rp_cl_main |
| rp_copy_attributes | Copy Matrix Attributes |
| rp_diagProfile | Diagonal Recurrence Profile |
| rp_empty | Empty results vector |
| rp_lineDist | Line length distributions |
| rp_measures | Get (C)RQA measures based on a binary matrix |
| rp_measures_main | Get (C)RQA measures from a Recurrence Matrix |
| rp_nzdiags | rp_nzdiags |
| rp_plot | Plot (thresholded) distance matrix as a recurrence plot |
| rp_prep | Prepare matrix |
| rp_size | rp_size |
| rqa_calc | rqa_calc |
| rqa_fast | Fast rqa |
| rqa_getSeries | Get embedded series for rp() and rqa() |
| rqa_lineDist | Fast line dist |
| rqa_measures | Fast RQA |
| rqa_par | Massively Parallel RQA analysis |
| rqa_plot | Plot large RP |
| rqa_stitchRows | Stitch rows |
| sa2fd_dfa | Informed Dimension estimate from DFA slope (H) |
| sa2fd_psd | Informed Dimension estimate from Spectral Slope (aplha) |
| sa2fd_sda | Informed Dimension estimate from SDA slope. |
| scale_log | scale_log |
| SDA | Standardised Dispersion Analysis |
| set_command_line_rp | Set command line RQA executable |
| setTheiler | Set theiler window on a distance matrix or recurrence matrix. |
| SWtestE | Small World test |
| symbolize | Convert numeric vectors to symbolic vectors. |
| symHelper | Correct for plateaus in symbolic series |
| tidyeval | Tidy eval helpers |
| ts_center | Center a vector |
| ts_changeindex | Find change indices |
| ts_checkfix | Check and/or Fix a vector |
| ts_coarsegrain | Course grain a time series |
| ts_cp | Change Profile |
| ts_detrend | Detrend a time series |
| ts_diff | Derivative of time series |
| ts_discrete | Discrete representation |
| ts_duration | Time series to Duration series |
| ts_embed | Delay embedding of a time series |
| ts_integrate | Create a timeseries profile |
| ts_levels | Detect levels in time series |
| ts_peaks | Find Peaks or Wells |
| ts_permtest_block | Permutation Test: Block Randomisation |
| ts_permtest_transmat | Permutation Test: Transition Matrix |
| ts_rasterize | Turn a 1D time series vector into a 2D curve |
| ts_sd | Standard Deviation estimates |
| ts_slice | Slice a Matrix |
| ts_slope | Calculate Kendall's tau in sliding window or around change... |
| ts_slopes | Detect slopes in time series |
| ts_standardise | Standardise a vector |
| ts_sumorder | Adjust time series by summation order |
| ts_symbolic | Symbolic representation |
| ts_transmat | Transition matrix |
| ts_trimfill | Trim or Fill Vectors |
| ts_windower | Get sliding window indices |
| var_win | Windowed variance |
