PP.test
PhillipsPerron Test for Unit Roots
Computes the PhillipsPerron test for the null hypothesis that
x
has a unit root against a stationary alternative.
 Keywords
 ts
Usage
PP.test(x, lshort = TRUE)
Arguments
 x
 a numeric vector or univariate time series.
 lshort
 a logical indicating whether the short or long version of the truncation lag parameter is used.
Details
The general regression equation which incorporates a constant and a
linear trend is used and the corrected tstatistic for a first order
autoregressive coefficient equals one is computed. To estimate
sigma^2
the NeweyWest estimator is used. If lshort
is TRUE
, then the truncation lag parameter is set to
trunc(4*(n/100)^0.25)
, otherwise
trunc(12*(n/100)^0.25)
is used. The pvalues are
interpolated from Table 4.2, page 103 of Banerjee et al
(1993).
Missing values are not handled.
Value

A list with class
 statistic
 the value of the test statistic.
 parameter
 the truncation lag parameter.
 p.value
 the pvalue of the test.
 method
 a character string indicating what type of test was performed.
 data.name
 a character string giving the name of the data.
"htest"
containing the following components:
References
A. Banerjee, J. J. Dolado, J. W. Galbraith, and D. F. Hendry (1993) Cointegration, Error Correction, and the Econometric Analysis of NonStationary Data, Oxford University Press, Oxford.
P. Perron (1988) Trends and random walks in macroeconomic time series. Journal of Economic Dynamics and Control 12, 297332.
Examples
library(stats)
x < rnorm(1000)
PP.test(x)
y < cumsum(x) # has unit root
PP.test(y)