Representation of class ca.jo
This class contains the relevant information by applying the Johansen procedure to a matrix of time series data. class
latin1
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 .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.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
.
Bernhard Pfaff
Useful links