I have 2 time series and I am using ccf
to find the cross correlation between them.
ccf(ts1, ts2)
lists the cross-correlations for all time lags. H
I thought I'd redo the above function but have it find the absolute max correlation that returns the original correlation (positive or negative). I also maxed out (nearly) the number of lags.
Find_Abs_Max_CCF<- function(a,b)
{
d <- ccf(a, b, plot = FALSE, lag.max = length(a)-5)
cor = d$acf[,,1]
abscor = abs(d$acf[,,1])
lag = d$lag[,,1]
res = data.frame(cor,lag)
absres = data.frame(abscor,lag)
absres_max = res[which.max(absres$abscor),]
return(absres_max)
}
Because 3 is more than 4, I also had a stab at modifying this function, this time by implementing an idea from here:
ccfmax <- function(a, b, e=0)
{
d <- ccf(a, b, plot = FALSE, lag.max = length(a)/2)
cor = d$acf[,,1]
abscor = abs(d$acf[,,1])
lag = d$lag[,,1]
res = data.frame(cor, lag)
absres = data.frame(abscor, lag)
maxcor = max(absres$abscor)
absres_max = res[which(absres$abscor >= maxcor-maxcor*e &
absres$abscor <= maxcor+maxcor*e),]
return(absres_max)
}
Essentially an "error" term is added, so that if there are several values close to the maximum, they all get returned, eg:
ayy <- jitter(cos((1:360)/5), 100)
bee <- jitter(sin((1:360)/5), 100)
ccfmax(ayy, bee, 0.02)
cor lag
348 0.9778319 -8
349 0.9670333 -7
363 -0.9650827 7
364 -0.9763180 8
If no value for e
is given it is taken to be zero, and the function behaves just like the one nvogen posted.
I've modified the original solution as well, in order to loop over the function and output the values corresponding to a character vector of indices (x):
abs.max.ccf <- function(x,a,b) {
d <- ccf(a, b, plot=FALSE, lag.max=length(a)-5)
cor <- d$acf[,,1]
abscor <- abs(d$acf[,,1])
lag <- d$lag[,,1]
abs.cor.max <- abscor[which.max(abscor)]
abs.cor.max.lag <- lag[which.max(abscor)]
return(c(x, abs.cor.max, abs.cor.max.lag))
}
I removed the data.frame
part within the function, as it is unnecessarily slow. To loop over each column in a data.frame
and return the results to a new data.frame
, I use this method:
max.ccf <- lapply(colnames(df), function(x) unlist(abs.max.ccf(x, df$y, df[x])))
max.ccf <- data.frame(do.call(rbind, max.ccf))
colnames(max.ccf) <- c('Index','Cor','Lag')
Posting the answer http://r.789695.n4.nabble.com/ccf-function-td2288257.html
Find_Max_CCF<- function(a,b)
{
d <- ccf(a, b, plot = FALSE)
cor = d$acf[,,1]
lag = d$lag[,,1]
res = data.frame(cor,lag)
res_max = res[which.max(res$cor),]
return(res_max)
}