Methods for Function summary in Package ‘urca’
Summarises the outcome of unit root/cointegration tests by creating a new object of class sumurca.
The test type, its statistic, the test regression and the critical values for the Augmented Dickey and Fuller test are returned.
The test type, its statistic and the
critical values for the Elliott, Rothenberg \& Stock test are
returned. In case of test "DF-GLS" the summary output
of the test regression is provided, too.
The test statistic, the critical value as well as the test type and the number of lags used for error correction for the Kwiatkowski et al. unit root test is returned.
The "trace" or "eigen" statistic,
the critical values as well as the eigenvalues, eigenvectors and
the loading matrix of the Johansen procedure are reported.
The test statistic of a restricted VAR with respect to \bold{α} and/or \bold{β} with p-value and degrees of freedom is reported. Furthermore, the restriction matrix(ces), the eigenvalues and eigenvectors as well as the loading matrix are returned.
The "Pz" or "Pu" statistic,
the critical values as well as the summary output of the test
regression for the Phillips \& Ouliaris cointegration test.
The Z statistic, the critical values as well as the summary output of the test regression for the Phillips \& Perron test, as well as the test statistics for the coefficients of the deterministic part is returned.
The relevant tau statistic, the critical values as well as the summary output of the test regression for the augmented Dickey-Fuller test is returned.
The test statistic, the critical value as well as the summary output of the test regression for the Schmidt \& Phillips test is returned.
The test statistic, the critical values as well as the summary output of the test regression for the Zivot \& Andrews test is returned.
Bernhard Pfaff
data(nporg) gnp <- na.omit(nporg[, "gnp.r"]) gnp.l <- log(gnp) # ers.gnp <- ur.ers(gnp, type="DF-GLS", model="trend", lag.max=4) summary(ers.gnp) # kpss.gnp <- ur.kpss(gnp.l, type="tau", lags="short") summary(kpss.gnp) # pp.gnp <- ur.pp(gnp, type="Z-tau", model="trend", lags="short") summary(pp.gnp) # df.gnp <- ur.df(gnp, type="trend", lags=4) summary(df.gnp) # sp.gnp <- ur.sp(gnp, type="tau", pol.deg=1, signif=0.01) summary(sp.gnp) # za.gnp <- ur.za(gnp, model="both", lag=2) summary(za.gnp) # data(finland) sjf <- finland sjf.vecm <- ca.jo(sjf, ecdet="none", type="eigen", K=2, season=4) summary(sjf.vecm) # HF0 <- matrix(c(-1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1), c(4,3)) summary(blrtest(sjf.vecm, H=HF0, r=3))
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