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