All functions

ColouredNoise

Coloured noise data

RNG

Random Number Sequences

SWtestE()

Small World test

ac_win()

Windowed autocorrelation function

add_alpha()

Add transparency to a colour

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

dc_ccp()

Cumulative Complexity Peaks (CCP)

dc_d()

Distribution Uniformity Distribution Uniformity is one of two components of which the product is the Dynamic Complexity measure.

dc_f()

Fluctuation Intensity

dc_win()

Dynamic Complexity

di2bi()

Distance to binary matrix

di2we()

Distance 2 weighted matrix

dist_hamming()

Calculate Hamming distance

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_radius()

Estimate Radius.

fd_RR()

Relative Roughness

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_psd()

Power Spectral Density Slope (PSD).

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)

fnn()

False Nearest Neighbours

getColours()

Get some nice colours

getPairs()

Get all combinations

get_os()

Which OS is running?

growth_ac()

Examples of dynamical growth models (maps)

growth_ac_cond()

Examples of conditional dynamical growth models (maps)

layout_as_spiral()

Layout a graph on a spiral

make_spiral_graph()

Make Spiral Graph

manyAnalystsESM

Data from the Many Analysts study.

mat2ind()

Matrix to indexed data frame

mi_interlayer()

Inter-layer mutual information

mi_mat()

Mutual Information variations

mif()

Mutual Information Function

mrn()

Multiplex Recurrence Network

mrn_plot()

Mutliplex 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

plotDC_ccp()

Plot Cumulative Complexity Peaks

plotDC_lvl()

Plot Peaks versus Levels

plotDC_res()

Plot Complexity Resonance Diagram

plotFD_loglog()

Plot output from fluctuation analyses based on log-log regression

plotMRN_win()

Plot windowed Multiplex Recurrence Network measures

plotNET_BA()

Example of Barabasi scale-free network

plotNET_SW()

Example of Strogatz-Watts small-world network

plotNET_groupColour()

Vertex and Edge Group Colours

plotNET_groupWeight()

Set Edge weights by group

plotNET_prep()

Plot Network Based on RQA

plotRED_acf()

Plot ACF and PACF

plotRED_mif()

Plot various MI functions

plotSUR_hist()

Surrogate Test

plotTS_multi()

Plot Multivariate Time Series Data

repmat()

Repeat Copies of a Matrix

rn()

Create a Recurrence Network Matrix

rn_measures()

Recurrence Network Measures

rn_plot()

Plot (thresholded) distance matrix as a network

rn_recSpec()

Recurrence Time Spectrum

rn_strengthDist()

Strength versus Degree scaling relation

rp()

Create a Distance Matrix

rp_cl()

Fast (C)RQA (command line crp)

rp_copy_attributes()

Copy Matrix Attributes

rp_diagProfile()

Diagonal Recurrence Profile

rp_lineDist()

Line length distributions

rp_measures()

Get (C)RQA measures based on a binary matrix

rp_nzdiags()

rp_nzdiags

rp_plot()

Plot (thresholded) distance matrix as a recurrence plot

rp_size()

rp_size

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.

set_command_line_rp()

Set command line RQA executable

ts_center()

Center a vector

ts_changeindex()

Find change indices

ts_checkfix()

Check and/or Fix a vector

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_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