Create a Distance Matrix

rp(
  y1,
  y2 = NULL,
  emDim = 1,
  emLag = 1,
  emRad = NULL,
  theiler = NA,
  to.ts = NULL,
  order.by = NULL,
  to.sparse = TRUE,
  weighted = FALSE,
  weightedBy = "si",
  method = c("Euclidean", "SBD")[1],
  rescaleDist = c("none", "maxDist", "meanDist")[1],
  targetValue = 0.05,
  chromatic = FALSE,
  returnMeasures = FALSE,
  doPlot = FALSE,
  doEmbed = TRUE,
  silent = TRUE,
  ...
)

Arguments

y1

A numeric vector or time series

y2

A numeric vector or time series for cross recurrence

emDim

The embedding dimensions

emLag

The embedding lag

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)

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.

to.ts

Should y1 and y2 be converted to time series objects?

order.by

If to.ts = TRUE, pass a vector of the same length as y1 and y2. It will be used as the time index, if NA the vector indices will be used to represent time.

to.sparse

Should sparse matrices be used?

weighted

If FALSE a binary matrix will be returned. If TRUE every value larger than emRad will be 0, but values smaller than emRad will be retained (default = FALSE)

weightedBy

After setting values smaller than emRad to 0, what should the recurrent values represent? The default is to use the state space similarity (distance/proximity) values as weights ("si"). Other option are "rt" for recurrence time and "rf" for recurrence time frequency (default = "si")

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")

rescaleDist

Should the distance matrix be rescaled? Options are "none", "maxDist" to create a unit scale, "meanScale" to creat z-scores based on the mean distance. (default = "none")

targetValue

A value passed to est_radius(...,type="fixed", targetMeasure="RR") if is.na(emRad)==TRUE.

chromatic

Perform a chromatic RQA. This assumes the recurring values represent the labels of an unordered categorical variable (default = FALSE)

returnMeasures

Should the output of rp_measures() be returned as an attribute "measures" to the matrix? If silent = FALSE results will also be output to the console. (default = FALSE)

doPlot

Plot the matrix by calling rp_plot() with default settings

doEmbed

If FALSE, a distance matrix will be returned that is not embedded by emDim and emLag (Multidimensional RQA). If y1 and/or y2 are data frames, the columns will be used as the state space dimensions (default = TRUE)

silent

Silent-ish mode

...

Any parameters to pass to rp_plot() if doPlot = TRUE

Value

A (Coss-) Recurrence matrix with attributes:

emdims1 and emdims2 - A matrix of surrogate dimensions
emdims1.name and emdims2.name - Names of surrogate dimensions
method and call - The distance method used by proxy::dist()
weighted - Whether a weighted matrix is returned
emDim, emLag and emRad - The embedding parameters
AUTO - Whether the matrix represents AUTO recurrence

Note

The calculation of the (C)RQA measures in casnet can be different from other packages. For example, depending on the value of theiler the main diagonal can be included or excluded from the calculations, whereas some software will always include the diagonal.

Create a Distance Matrix

Arguments

Value

Note

See also