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\name{ur.pp}
\alias{ur.pp}
\encoding{latin1}
\title{Phillips \& Perron Unit Root Test}
\description{
Performs the Phillips \& Perron unit root test. Beside the Z
statistics Z-alpha and Z-tau, the Z statistics for the deterministic
part of the test regression are computed, too.
}
\usage{
ur.pp(x, type = c("Z-alpha", "Z-tau"), model = c("constant", "trend"),
lags = c("short", "long"), use.lag = NULL)
}
\arguments{
\item{x}{Vector to be tested for a unit root.}
\item{type}{Test type, either \code{"Z-alpha"} or \code{"Z-tau"}.}
\item{model}{Determines the deterministic part in the test regression.}
\item{lags}{Lags used for correction of error term.}
\item{use.lag}{Use of a different lag number, specified by the user.}
}
\details{
The function \code{ur.pp()} computes the Phillips \& Perron test. For
correction of the error term a Bartlett window is used.
}
\value{
An object of class \code{ur.pp}.
}
\references{
Phillips, P.C.B. and Perron, P. (1988), Testing for a unit root in
time series regression, \emph{Biometrika}, \bold{75(2)}, 335--346.
MacKinnon, J.G. (1991), Critical Values for Cointegration Tests,
\emph{Long-Run Economic Relationships}, eds. R.F. Engle and
C.W.J. Granger, London, Oxford, 267--276.
Download possible at: \url{http://cowles.econ.yale.edu/}, see rubric
'Discussion Papers (CFDPs)' and
\url{http://www.econ.ucsd.edu/papers/files/90-4.pdf}.
}
\seealso{\code{\link{ur.pp-class}}.}
\examples{
data(nporg)
gnp <- na.omit(nporg[, "gnp.r"])
pp.gnp <- ur.pp(gnp, type="Z-tau", model="trend", lags="short")
summary(pp.gnp)
}
\author{Bernhard Pfaff}
\keyword{regression}
|
