is that 'x' is level or trend stationary. I did this
s-rnorm(1000)
kpss.test(s)
KPSS Test for Level Stationarity
data: s
KPSS Level = 0.0429, Truncation lag parameter = 7,
p-value = 0.1
Warning message:
p-value greater than printed p-value in:
kpss.test(s)
My
As help(kpss.test) tells you: kpss.test() approximates the p values by
interpolation from a simulated table of critical values. As p values
larger than 0.1 are typically regarded to be non-significant and p
values smaller than 0.01 are typically regarded to be highly
significant, the corresponding
Understood!
And thanks!
Weiguang
--- Achim Zeileis [EMAIL PROTECTED]
wrote:
As help(kpss.test) tells you: kpss.test()
approximates the p values by
interpolation from a simulated table of critical
values. As p values
larger than 0.1 are typically regarded to be
non-significant and p
