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% File src/library/stats/man/pp.test.Rd
% Part of the R package, https://www.R-project.org
% Copyright 1995-2018 R Core Team
% Distributed under GPL 2 or later
\name{PP.test}
\alias{PP.test}
\title{Phillips-Perron Test for Unit Roots}
\usage{
PP.test(x, lshort = TRUE)
}
\arguments{
\item{x}{a numeric vector or univariate time series.}
\item{lshort}{a logical indicating whether the short or long version
of the truncation lag parameter is used.}
}
\description{
Computes the Phillips-Perron test for the null hypothesis that
\code{x} has a unit root against a stationary alternative.
}
\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
\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 4.2, page 103 of Banerjee \emph{et al}
(1993).
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.}
}
\references{
A. Banerjee, J. J. Dolado, J. W. Galbraith, and D. F. Hendry (1993).
\emph{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.
\emph{Journal of Economic Dynamics and Control}, \bold{12}, 297--332.
\doi{10.1016/0165-1889(88)90043-7}.
}
\author{A. Trapletti}
\examples{
x <- rnorm(1000)
PP.test(x)
y <- cumsum(x) # has unit root
PP.test(y)
}
\keyword{ts}