rqa_calc: rqa_calc

In FredHasselman/casnet: A Toolbox for Studying Complex Adaptive Systems and Networks

rqa_calc

Description

rqa_calc

Usage

rqa_calc(
  y1,
  y2 = NA,
  emRad = NULL,
  DLmin = 2,
  VLmin = 2,
  HLmin = 2,
  DLmax = NA,
  VLmax = NA,
  HLmax = NA,
  theiler = NA,
  corridor = NA,
  AUTO = NULL,
  method = "Euclidean",
  includeDiagonal = NA,
  chromatic = FALSE,
  anisotropyHV = FALSE,
  asymmetryUL = FALSE,
  returnUL = FALSE,
  recurrenceTimes = FALSE,
  distributions = FALSE
)

Arguments

y1	A numeric vector or time series
y2	A numeric vector or time series for cross recurrence
emRad	The threshold (emRad) to apply to the distance matrix to create a binary or weighted matrix. If NULL, an unthresholded matrix will be created (default = NULL)
DLmin	Minimal diagonal line length (default = 2)
VLmin	Minimal vertical line length (default = 2)
HLmin	Minimal horizontal line length (default = 2)
DLmax	Maximal diagonal line length (default = length of diagonal -1)
VLmax	Maximal vertical line length (default = length of diagonal -1)
HLmax	Maximal horizontal line length (default = length of diagonal -1)
theiler	Use a theiler window around the main diagonal (Line of Identity/Synchronisation) to remove auto-correlations at short time-lags: 0 will include the main diagonal in all RQA measure calculations. 1 will remove the main diagonal from all RQA measure calculations. NA (default), will check if the matrix is symmetrical , if so, it will remove the diagonal by setting theiler = 1 (Line of Identity, Auto-RQA), if it is not symmetrical (Line of Synchronisation, Cross-RQA) it will set theiler = 0. A value greater than 1 will remove that many diagonals around and including the diagonal from all RQA measure calculations. So theiler = 2 means exclude 2 diagonals around the main diagonal, including the main diagonal itself: ⁠[-1,0,1]⁠. If theiler is a numeric vector of length(theiler) == 2 it is possible to exclude an asymmetrical window. The values are interpreted as end points in a sequence of diagonal ID's, e.g. theiler = c(-1,5) will exclude ⁠[-1,0,1,2,3,4,5]⁠. If length(theiler) > 2, the values will be considered individual diagonal ID's, e.g. theiler = c(-3,-1,0,2,5), will exclude only those specific ID's. Also see the note.
corridor	corridor
AUTO	Auto-recurrence? (default = FALSE)
method	Distance measure to use. Any option that is valid for argument method of proxy::dist(). Type proxy::pr_DB$get_entries() to see a list of all the options. Common methods are: ⁠"Euclidean", "Manhattan", "Minkowski", "Chebysev"⁠ (or the same but shorter: ⁠"L2","L1","Lp", "max"⁠ distance). To use the shape based distance for phase-based recurrence use "SBD" (default = "Euclidean")
chromatic	Perform a chromatic RQA. This assumes the recurring values represent the labels of an unordered categorical variable (default = FALSE)
anisotropyHV	Return anisotropy ratio measures based on Horizontal and Vertical lines. The ratios are calculated as (horizontal - vertical) / (horizontal + vertical). So a value of 0 means no anisotropy, negative ratios indicate the measures based on vertical lines had higher values, positive ratios indicate the measures based on horizontal lines had higher values (default = FALSE)
asymmetryUL	Return asymmetry ratio measures based on Upper and Lower triangles. The ratios are calculated as (upper - lower) / (upper + lower). So a value of 0 means no asymmetry, negative ratios indicate the measures based on the lower triangle had the higher values, positive ratios indicate measures based on the upper triangle had higher values (default = FALSE)
returnUL	Return the (C)RQA values for the upper and lower triangle on which asymmetry ratio calculations are based? (default = FALSE)
recurrenceTimes	Return measures based on 'white lines', the recurrence times (default = FALSE)
distributions	Return line length distributions.

Value

CRQA measures and matrices of line distributions (if requested) based on massively parallel analysis, without building the recurrence matrix.

FredHasselman/casnet documentation built on April 20, 2024, 3:05 p.m.