"mu"
or a constant with linear trend "tau"
.
ur.kpss(y, type = c("mu", "tau"), lags = c("short", "long", "nil"), use.lag = NULL)
ur.kpss
.
lags="short"
sets the number of lags to $\root 4 \of {4
\times (n/100)}$,
whereas lags="long"
sets the number of lags to $\root 4 \of
{12 \times (n/100)}$. If lags="nil"
is choosen, then no error
correction is made. Furthermore, one can specify a different number of
maximum lags by setting use.lag
accordingly.
Download possible at: http://cowles.econ.yale.edu/, see rubric 'Discussion Papers (CFDPs)'.
ur.kpss-class
data(nporg) gnp <- na.omit(nporg[, "gnp.r"]) gnp.l <- log(gnp) kpss.gnp <- ur.kpss(gnp.l, type="tau", lags="short") summary(kpss.gnp)
Run the code above in your browser using DataCamp Workspace