PP.test
Phillips-Perron Test for Unit Roots
Computes the Phillips-Perron 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 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, 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 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.
"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 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
library(stats)
x <- rnorm(1000)
PP.test(x)
y <- cumsum(x) # has unit root
PP.test(y)