library(quantmod)
data_origin=read.csv("data.csv",header = F)
data<-data.frame(Open=data_origin[,2],High=data_origin[,3],Low=data_origin[,4],Close=data_origin[,5],Volume=data_origin[,7],Adjusted=data_origin[,6])
rownames(data)<-as.Date(as.character(data_origin$V1),"%Y%m%d")
chartSeries(data)
先是对X和Z做处理：xmean <- apply(X,2,mean)zmean <- apply(Z,2,mean)
xsd <- apply(X,2,sd)zsd <- apply(Z,2,sd)
xsd[xsd==0] <- 1zsd[zsd==0] <- 1
Xs <- X - matrix(xmean, nrow(X), ncol(X), byrow=T)
Zs <- Z - matrix(zmean, nrow(Z), ncol(Z), byrow=T)
Xs <- Xs * matrix(1/xsd, nrow(X), ncol(X), byrow=T)
Zs <- Zs * matrix(1/zsd, nrow(Z), ncol(Z), byrow=T)
然后调用PMA包中的CCA函数：
res <- CCA(x=Xs,z=Zs,typex="standard", typez="standard", penaltyx=0.04, penaltyz=0.04, niter=15, K=80, trace=T, standardize=F)
程序就会提示出错：Error in CheckVs(v, x, z, K) : Problem computing SVD.
