Representation of class ca.jo
This class contains the relevant information by applying the Johansen procedure to a matrix of time series data.
x
:Object of class "ANY"
: A data matrix, or an
object that can be coerced to it.
Z0
:Object of class "matrix"
: The matrix of the
differenced series.
Z1
:Object of class "matrix"
: The regressor
matrix, except for the lagged variables in levels.
ZK
:Object of class "matrix"
: The matrix of the
lagged variables in levels.
type
:Object of class "character"
: The type of the
test, either "trace"
or "eigen"
.
model
:Object of class "character"
: The model
description in prose, with respect to the inclusion of a linear
trend.
ecdet
:Object of class "character"
: Specifies
the deterministic term to be included in the cointegration
relation. This can be either "none", "const", or "trend".
lag
:Object of class "integer"
: The lag order
for the variables in levels.
P
:Object of class "integer"
: The count of
variables.
season
:Object of class "ANY"
: The frequency of
the data, if seasonal dummies should be included, otherwise NULL.
dumvar
:Object of class "ANY"
: A matrix
containing dummy variables. The row dimension must be equal to
x
, otherwise NULL.
cval
:Object of class "ANY"
: The critical
values of the test at the 1%, 5% and 10% level of significance.
teststat
:Object of class "ANY"
: The values
of the test statistics.
lambda
:Object of class "vector"
: The eigenvalues.
Vorg
:Object of class "matrix"
: The matrix of
eigenvectors, such that \hat V'S_{kk}\hat V = I.
V
:Object of class "matrix"
: The matrix of
eigenvectors, normalised with respect to the first variable.
W
:Object of class "matrix"
: The matrix of
loading weights.
PI
:Object of class "matrix"
: The coeffcient
matrix of the lagged variables in levels.
DELTA
:Object of class "matrix"
: The
variance/covarinace matrix of V
.
GAMMA
:Object of class "matrix"
: The
coeffecient matrix of Z1
.
R0
:Object of class "matrix"
: The matrix of
residuals from the regressions in differences.
RK
:Object of class "matrix"
: The matrix of
residuals from the regression in lagged levels.
bp
:Object of class "ANY"
: Potential break
point, only set if function cajolst
is called, otherwise
NA
.
test.name
:Object of class "character"
: The
name of the test, i.e. ‘Johansen-Procedure’.
spec
:Object of class "character"
: The
specification of the VECM.
call
:Object of class "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
:test statistic.
summary
:like show, but critical values, eigenvectors and loading matrix added.
plot
:The series of the VAR and their potential cointegration relations.
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
.
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