Use rp_measures
Arguments
- RM
A distance matrix (set
emRad = NA
to estimate a radius), or a matrix of zeroes and ones- emRad
Threshold for distance value that counts as a recurrence (ignored is
RM
is a binary matrix)- 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)
- AUTO
Auto-recurrence? (default =
FALSE
)- 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 settingtheiler = 1
(Line of Identity, Auto-RQA), if it is not symmetrical (Line of Synchronisation, Cross-RQA) it will settheiler = 0
.A value greater than
1
will remove that many diagonals around and including the diagonal from all RQA measure calculations. Sotheiler = 2
means exclude2
diagonals around the main diagonal, including the main diagonal itself:[-1,0,1]
. Iftheiler
is a numeric vector oflength(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]
. Iflength(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.
- chromatic
Force chromatic RQA? If
NA
the value of theRM
attribute"chromatic"
will be used, if present (default =NA
)- matrices
Return matrices? (default =
FALSE
)- Nboot
How many bootstrap replications? (default =
NULL
)- CL
Confidence limit for bootstrap results (default =
.95
)
See also
Other Recurrence Quantification Analysis:
rp_cl()
,
rp_measures()