Description Usage Arguments Value Author(s) References Examples
Compute multiple wavelet coherence
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 
y 
time series 1 in matrix format ( 
x1 
time series 2 in matrix format ( 
x2 
time series 3 in matrix format ( 
pad 
pad the values will with zeros to increase the speed of the transform. Default is TRUE. 
dj 
spacing between successive scales. Default is 1/12. 
s0 
smallest scale of the wavelet. Default is 
J1 
number of scales  1. 
max.scale 
maximum scale. Computed automatically if left unspecified. 
mother 
type of mother wavelet function to use. Can be set to

param 
nondimensional parameter specific to the wavelet function. 
lag1 
vector containing the AR(1) coefficient of each time series. 
sig.level 
significance level. Default is 
sig.test 
type of significance test. If set to 0, use a regular χ^2 test. If set to 1, then perform a timeaverage test. If set to 2, then do a scaleaverage test. 
nrands 
number of Monte Carlo randomizations. Default is 300. 
quiet 
Do not display progress bar. Default is 
Return a vectorwavelet
object containing:
coi 
matrix containg cone of influence 
rsq 
matrix of wavelet coherence 
phase 
matrix of phases 
period 
vector of periods 
scale 
vector of scales 
dt 
length of a time step 
t 
vector of times 
xaxis 
vector of values used to plot xaxis 
s0 
smallest scale of the wavelet 
dj 
spacing between successive scales 
mother 
mother wavelet used 
type 
type of 
signif 
matrix containg 
Tunc Oygur (info@tuncoygur.com.tr)
Code based on MWC MATLAB package written by Eric K. W. Ng and Johnny C. L. Chan.
T. Oygur, G. Unal.. Vector wavelet coherence for multiple time series. Int. J. Dynam. Control (2020).
T. Oygur, G. Unal. 2017. The large fluctuations of the stock return and financial crises evidence from Turkey: using wavelet coherency and VARMA modeling to forecast stock return. Fluctuation and Noise Letters
Ng, Eric KW and Chan, Johnny CL. 2012. Geophysical applications of partial wavelet coherence and multiple wavelet coherence. Journal of Atmospheric and Oceanic Technology 2912:1845–1853.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24  old.par < par(no.readonly=TRUE)
t < (100:100)
y < sin(t*2*pi)+sin(t*2*pi/4)+sin(t*2*pi/8)+sin(t*2*pi/16)+sin(t*2*pi/32)+sin(t*2*pi/64)
x1 < sin(t*2*pi/8)
x2 < sin(t*2*pi/32)
y < cbind(t,y)
x1 < cbind(t,x1)
x2 < cbind(t,x2)
## Multiple wavelet coherence
result < mwc(y, x1, x2, nrands = 10)
result < mwc(y, x1, x2)
## Plot wavelet coherence and make room to the right for the color bar
## Note: plot function can be used instead of plot.vectorwavelet
par(oma = c(0, 0, 0, 1), mar = c(5, 4, 4, 5) + 0.1, pin = c(3,3))
plot.vectorwavelet(result, plot.cb = TRUE, main = "Plot multiple wavelet coherence")
par(old.par)

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