plot_local.multiple.cross.regression <- #3.1.0
function(Lst, lmax, nsig=2, xaxt="s"){
##Producing regression plot
# requireNamespace(magrittr)
if (xaxt[1]!="s"){
at <- xaxt[[1]]
label <- xaxt[[2]]
xaxt <- "n"
}
val <- Lst$cor$vals
reg.vals <- Lst$reg$rval[,,-1] #exclude constant
reg.stdv <- Lst$reg$rstd[,,-1]
reg.lows <- Lst$reg$rlow[,,-1]
reg.upps <- Lst$reg$rupp[,,-1]
reg.pval <- Lst$reg$rpva[,,-1]
reg.order <- Lst$reg$rord[,,-1]-1
reg.order[reg.order==0] <-
reg.vals[reg.order==0] <- #exclude dependent variable
reg.stdv[reg.order==0] <-
reg.lows[reg.order==0] <-
reg.upps[reg.order==0] <-
reg.pval[reg.order==0] <- NA
lag.max <- trunc((ncol(val)-1)/2)
lag0 <- lag.max+1
YmaxR <- Lst$YmaxR
N <- length(YmaxR)
xxnames <- names(Lst$data)
lag.labs <- c(paste("lead",lag.max:1),paste("lag",0:lag.max))
reg.vars <- t(matrix(xxnames,length(Lst$data),N))
reg.sel <- reg.order<=nsig & reg.pval<=0.05 #select firs nsig 5%signif. predictors
reg.vals.sig <- reg.vals*reg.sel
reg.lows.sig <- reg.lows*reg.sel
reg.upps.sig <- reg.upps*reg.sel
# reg.pval.sig <- reg.pval*reg.sel
reg.order.sig <- reg.order*reg.sel
reg.vals.sig[reg.vals.sig==0] <-
reg.lows.sig[reg.lows.sig==0] <-
reg.upps.sig[reg.upps.sig==0] <-
# reg.pval.sig[reg.pvals.sig==0] <-
reg.order.sig[reg.order.sig==0] <- NA
# requireNamespace(RColorBrewer)
mycolors <- RColorBrewer::brewer.pal(n=8, name="Dark2")
par(mfcol=c(lmax+1,2), las=1, pty="m", mar=c(2,3,1,0)+.1, oma=c(1.2,1.2,0,0))
ymin <- min(reg.vals,na.rm=TRUE) #head(unique(sort(reg.vals[,,-1])))[2]
ymax <- max(reg.vals,na.rm=TRUE)
mark <- paste0("\u00A9jfm-wavemulcor3.1.0_",Sys.time()," ")
for(i in c(-lmax:0,lmax:1)+lag0) {
matplot(1:N,reg.vals[,i,], ylim=c(ymin-0.1,ymax+0.1),
type="n", xaxt=xaxt, lty=3, col=8,
xlab="", ylab="", main=lag.labs[i])
# shade <- 1.96*reg.stdv %>% apply(1,max)
for (j in dim(reg.stdv)[3]:1){
shade <- 1.96*reg.stdv[,i,j]
polygon(c(1:N,rev(1:N)),c(-shade,rev(shade)), col=gray(0.8,alpha=0.2), border=NA)
}
matlines(1:N,reg.vals[,i,], lty=1, col=8)
if(abs(ymax-ymin)<3) lo<-2 else lo<-4
abline(h=seq(floor(ymin),ceiling(ymax),length.out=lo),col=8)
matlines(1:N, reg.vals.sig[,i,], lty=1, lwd=2, col=mycolors)
matlines(1:N, reg.lows.sig[,i,], lty=2, col=mycolors)
matlines(1:N, reg.upps.sig[,i,], lty=2, col=mycolors)
mtext(mark, side=1, line=-1, adj=1, col=rgb(0,0,0,.1),cex=.2)
col <- (reg.order[,i,]<=3)*1 +(reg.order[,i,]>3)*8
# xvar <- seq(1,N,M)
xvar <- t(t(which(abs(diff(sign(diff(reg.vals[,i,]))))==2,arr.ind=TRUE))+c(1,0))
text(xvar, reg.vals[xvar,i,], labels=reg.vars[xvar,], col=col,cex=.3)
text(xvar, reg.vals[xvar,i,], labels=reg.order[xvar,i,],pos=1, col=col,cex=.3)
if (length(unique(YmaxR))==1) {
mtext(xxnames[YmaxR][1], at=1, side=3, line=-1, cex=.5)
} else {
xvaru <- t(t(which(diff(sign(diff(as.matrix(val[,i]))))==-2))+1)
xvarl <- t(t(which(diff(sign(diff(as.matrix(val[,i]))))==2))+1)
# xvar <- t(t(which(abs(diff(sign(diff(as.matrix(val[,i])))))==2))+1)
# xvar2 <- xvar[-length(xvar)]+diff(xvar)/2
mtext(xxnames[YmaxR][xvaru], at=xvaru, side=3, line=-.5, cex=.3)
# mtext(xxnames[YmaxR][xvar2], at=xvar2, side=3, line=-1, cex=.5)
mtext(xxnames[YmaxR][xvarl], at=xvarl, side=3, line=-1, cex=.3)
}
if (xaxt!="s") axis(side=1, at=at, labels=label)
}
par(las=0)
mtext('time', side=1, outer=TRUE, adj=0.5)
mtext('Local Multiple Cross-Regression', side=2, outer=TRUE, adj=0.5)
return()
}
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