require(tseries)

#Rescaled covariance test
RCT_alt<-function(x,y,q,d1,d2){
	xx<-cumsum(x-mean(x))
	yy<-cumsum(y-mean(x))
	M<-(q)^(d1+d2)*cov(xx,yy)/(length(xx)*sum((1-abs(-q:q)/(q+1))*ccf(x,y,lag.max=q,type="covariance",plot=FALSE)$acf))
	return(M)
}


#Rescaled covariance test with MBB confidence intervals
#rep (MBB repetitions), bs (MBB window size), alpha (confidence level), CV1/CV2 (critical values for level alpha)
RCT_MBB<-function(x,y,d1,d2,q,rep,bs,alpha){
	M<-runif(rep+1)
	M[1]<-RCT_alt(x,y,q,d1,d2)
	for(i in 1:rep){
		b<-MBB(x,y,bs)
		M[i+1]<-RCT_alt(b[,1],b[,2],q,0,0)
	}
	CV1<-quantile(M[2:rep+1],probs=1-alpha/2)
	CV2<-quantile(M[2:rep+1],probs=alpha/2)
	p_val<-2*(0.5-abs((rank(M)[1]/(rep+1))-0.5))
	return(c(M[1],CV1,CV2,p_val))
}