# PP.test

0th

Percentile

##### 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 "htest" containing the following components:
• statisticthe value of the test statistic.
• parameterthe truncation lag parameter.
• p.valuethe p-value of the test.
• methoda character string indicating what type of test was performed.
• data.namea character string giving the name of the data.

##### 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.

• PP.test
##### Examples
library(stats) x <- rnorm(1000) PP.test(x) y <- cumsum(x) # has unit root PP.test(y)
Documentation reproduced from package stats, version 3.3, License: Part of R 3.3

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