| PP.test {ts} | R Documentation |
Phillips-Perron Unit Root Test
Description
Computes the Phillips-Perron test for the null hypothesis that
x has a unit root.
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 t-statistic for a first order
autoregressive coefficient equals one is computed. To estimate
sigma^2 the Newey-West 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 p-values are
interpolated from Table 4.2, p. 103 of Banerjee et al.
(1993).
Missing values are not handled.
Value
A list with class "htest" containing the following components:
statistic |
the value of the test statistic. |
parameter |
the truncation lag parameter. |
p.value |
the p-value 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. |
Author(s)
A. Trapletti
References
A. Banerjee, J. J. Dolado, J. W. Galbraith, and D. F. Hendry (1993): Cointegration, Error Correction, and the Econometric Analysis of Non-Stationary Data, Oxford University Press, Oxford.
P. Perron (1988): Trends and Random Walks in Macroeconomic Time Series. Journal of Economic Dynamics and Control 12, 297-332.
Examples
x <- rnorm(1000)
PP.test(x)
y <- cumsum(x) # has unit root
PP.test(y)