I have two time-series from two different years and would like to statistically test whether they are different in values despite showing the same/similar trends. I'm really new to time-series analysis (and R), so please bear with me. So far, all I've done is create the actual time-series from my data and applied a simple moving average (with n=10).
I've already searched and googled, but all I really can find are prediction models, but that's not really what I'm interested in. I'm more interested in a statistical test comparing the two (e.g. binned by month), however I'm not sure what the appropriate approach and test are.
Here is some of the code:
k<-read.csv("~/Desktop/k.csv") k14<-k[,2] k14f<-na.fill(k14,"extend") k14ts<-ts(k14f, frequency=365, start=c(2014,305)) k14tsSMA10<-SMA(k14ts, n=10) k15<-[,3] k15f<-na.fill(k15,"extend") k15ts<-ts(k15f, frequency=365, start=c(2015,305)) k15tsSMA10<-SMA(k15ts, n=10) kSMA<-cbind(k14tsSMA10, k15tsSMA10) ts.plot(kSMA)