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\name{ca.jo-class}
\docType{class}
\alias{ca.jo-class}
\encoding{latin1}
\title{Representation of class ca.jo}
\description{
This class contains the relevant information by applying the Johansen
procedure to a matrix of time series data.
}
\section{Slots}{
\describe{
\item{\code{x}:}{Object of class \code{"ANY"}: A data matrix, or an
object that can be coerced to it.}
\item{\code{Z0}:}{Object of class \code{"matrix"}: The matrix of the
differenced series.}
\item{\code{Z1}:}{Object of class \code{"matrix"}: The regressor
matrix, except for the lagged variables in levels.}
\item{\code{ZK}:}{Object of class \code{"matrix"}: The matrix of the
lagged variables in levels.}
\item{\code{type}:}{Object of class \code{"character"}: The type of the
test, either \code{"trace"} or \code{"eigen"}.}
\item{\code{model}:}{Object of class \code{"character"}: The model
description in prose, with respect to the inclusion of a linear
trend.}
\item{\code{ecdet}:}{Object of class \code{"character"}: Specifies
the deterministic term to be included in the cointegration
relation. This can be either "none", "const", or "trend".}
\item{\code{lag}:}{Object of class \code{"integer"}: The lag order
for the variables in levels.}
\item{\code{P}:}{Object of class \code{"integer"}: The count of
variables.}
\item{\code{season}:}{Object of class \code{"ANY"}: The frequency of
the data, if seasonal dummies should be included, otherwise NULL.}
\item{\code{dumvar}:}{Object of class \code{"ANY"}: A matrix
containing dummy variables. The row dimension must be equal to
\code{x}, otherwise NULL.}
\item{\code{cval}:}{Object of class \code{"ANY"}: The critical
values of the test at the 1\%, 5\% and 10\% level of significance.}
\item{\code{teststat}:}{Object of class \code{"ANY"}: The values
of the test statistics.}
\item{\code{lambda}:}{Object of class \code{"vector"}: The eigenvalues.}
\item{\code{Vorg}:}{Object of class \code{"matrix"}: The matrix of
eigenvectors, such that \eqn{\hat V'S_{kk}\hat V = I}.}
\item{\code{V}:}{Object of class \code{"matrix"}: The matrix of
eigenvectors, normalised with respect to the first variable.}
\item{\code{W}:}{Object of class \code{"matrix"}: The matrix of
loading weights.}
\item{\code{PI}:}{Object of class \code{"matrix"}: The coeffcient
matrix of the lagged variables in levels.}
\item{\code{DELTA}:}{Object of class \code{"matrix"}: The
variance/covarinace matrix of \code{V}.}
\item{\code{GAMMA}:}{Object of class \code{"matrix"}: The
coeffecient matrix of \code{Z1}.}
\item{\code{R0}:}{Object of class \code{"matrix"}: The matrix of
residuals from the regressions in differences.}
\item{\code{RK}:}{Object of class \code{"matrix"}: The matrix of
residuals from the regression in lagged levels.}
\item{\code{bp}:}{Object of class \code{"ANY"}: Potential break
point, only set if function \code{cajolst} is called, otherwise
\code{NA}.}
\item{\code{test.name}:}{Object of class \code{"character"}: The
name of the test, \emph{i.e.} `Johansen-Procedure'.}
\item{\code{spec}:}{Object of class \code{"character"}: The
specification of the VECM.}
\item{\code{call}:}{Object of class \code{"call"}: The
call of function \code{ca.jo}.}
}
}
\section{Extends}{
Class \code{urca}, directly.
}
\section{Methods}{
Type \code{showMethods(classes="ca.jo")} at the R prompt for a
complete list of methods which are available for this class.
Useful methods include
\describe{
\item{\code{show}:}{test statistic.}
\item{\code{summary}:}{like show, but critical values, eigenvectors
and loading matrix added.}
\item{\code{plot}:}{The series of the VAR and their potential
cointegration relations.}
}
}
\references{
Johansen, S. (1988), Statistical Analysis of Cointegration Vectors,
\emph{Journal of Economic Dynamics and Control}, \bold{12}, 231--254.
Johansen, S. and Juselius, K. (1990), Maximum Likelihood Estimation and
Inference on Cointegration -- with Applications to the Demand for
Money, \emph{Oxford Bulletin of Economics and Statistics}, \bold{52,
2}, 169--210.
Johansen, S. (1991), Estimation and Hypothesis Testing of
Cointegration Vectors in Gaussian Vector Autoregressive Models,
\emph{Econometrica}, \bold{Vol. 59, No. 6}, 1551--1580.
}
\seealso{
\code{\link{ca.jo}}, \code{\link{plotres}} and \code{\link{urca-class}}.
}
\author{Bernhard Pfaff}
\keyword{classes}
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