# first generate a time-varying process
set.seed(879)
x=tvar2sim()
# calculate the lpacf
ans<-lpacf(x,lag.max=10,filter.number=2,family="DaubExPhase")
# then plot it at the first 10 lags at a couple of points in the data.
lpacf.plot(ans,atLag=1:10,atTime=c(150,350))
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