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\name{pp.test}
\alias{pp.test}
\title{Phillips--Perron Unit Root Test}
\description{
Computes the Phillips-Perron test for the null hypothesis that
\code{x} has a unit root.
}
\usage{
pp.test(x, alternative = c("stationary", "explosive"),
type = c("Z(alpha)", "Z(t_alpha)"), lshort = TRUE)
}
\arguments{
\item{x}{a numeric vector or univariate time series.}
\item{alternative}{indicates the alternative hypothesis and must be
one of \code{"stationary"} (default) or \code{"explosive"}. You can
specify just the initial letter.}
\item{type}{indicates which variant of the test is computed and must
be one of \code{"Z(alpha)"} (default) or \code{"Z(t_alpha)"}.}
\item{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 \code{Z(alpha)} or \code{Z(t_alpha)}
statistic for a first order autoregressive coefficient equals one are
computed. To estimate \code{sigma^2} the Newey-West estimator is
used. If \code{lshort} is \code{TRUE}, then the truncation lag
parameter is set to \code{trunc(4*(n/100)^0.25)}, otherwise
\code{trunc(12*(n/100)^0.25)} is used. The p-values are interpolated
from Table 4.1 and 4.2, p. 103 of
\bibcitet{R:Banerjee+Dolado+Galbraith:1993}. If the
computed statistic is outside the table of critical values, then a
warning message is generated.
Missing values are not handled.
}
\value{
A list with class \code{"htest"} containing the following components:
\item{statistic}{the value of the test statistic.}
\item{parameter}{the truncation lag parameter.}
\item{p.value}{the p-value of the test.}
\item{method}{a character string indicating what type of test was
performed.}
\item{data.name}{a character string giving the name of the data.}
\item{alternative}{a character string describing the alternative
hypothesis.}
}
\references{
\bibshow{R:Banerjee+Dolado+Galbraith:1993, Perron:1988}
}
\author{A. Trapletti}
\seealso{
\code{\link{adf.test}}
}
\examples{
x <- rnorm(1000) # no unit-root
pp.test(x)
y <- cumsum(x) # has unit root
pp.test(y)
}
\keyword{ts}
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