setwd('/Users/alexyuan/Documents/Shou Lab/timeseries_review/random_walk_correlation')
# import library
library(rEDM)
# import library
library(rEDM)
x = read.csv('raw/rw_xdata.csv', header=FALSE)
y = read.csv('raw/rw_ydata.csv', header=FALSE)
n_surr = 499
pvalues <- matrix(ncol=1, nrow=ncol(x))
for(idx in 1:ncol(x)){
rho = cor(x[,idx],y[,idx])
y_surr = make_surrogate_data(y[,idx], "ebisuzaki", n_surr)
rho_null = cor(x[,idx],y_surr)
pval = (sum(abs(rho_null) >= abs(rho)) + 1) / (length(rho_null) + 1)
pvalues[idx] <- pval
}
pvalues <- data.frame(pvalues)
write.csv(pvalues, 'raw/rw_ebitest.csv')
# same as ebitest_rw.R but for the AR(1) data
library(rEDM)
x = read.csv('raw/ar_xdata.csv', header=FALSE)
y = read.csv('raw/ar_ydata.csv', header=FALSE)
n_surr = 499
pvalues <- matrix(ncol=1, nrow=ncol(x))
for(idx in 1:ncol(x)){
rho = cor(x[,idx],y[,idx])
y_surr = make_surrogate_data(y[,idx], "ebisuzaki", n_surr)
rho_null = cor(x[,idx],y_surr)
pval = (sum(abs(rho_null) >= abs(rho)) + 1) / (length(rho_null) + 1)
pvalues[idx] <- pval
}
pvalues <- data.frame(pvalues)
write.csv(pvalues, 'raw/ar_ebitest.csv')
rEDM.version
rEDM
library(rEDM)
rEDM
rEDM.Version
rEDM.Version()
rEDM.__version__
sessionInfo()
help(ccm)
install(rEDM)
install.packages(rEDM)
install.packages(EDM)
install.packages
install.packages()
install.packages('rEDM')
install.packages("rEDM")
library(rEDM)
