PP.test                package:stats                R Documentation

Phillips-Perron Test for Unit Roots

Description:

     Computes the Phillips-Perron test for the null hypothesis that 'x'
     has a unit root against a stationary alternative.

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: 

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)

