rank.select(data, lag.max = 10, r.max = ncol(data) - 1,
include = c("const", "trend", "none", "both"),
fitMeasure = c("SSR", "LL"), sameSample = TRUE,
returnModels = FALSE) ## S3 method for class 'rank.select':
print(x, ...)
## S3 method for class 'rank.select':
summary(object, ...)
logLik.VECM
.rank.select
for the print
method.rank.select
for the
summary method.lags.max
) and lags (up to
lags.max
). This method has been shown to be useful
to select simultaneously the rank and the lags, see
references. -Cheng X and Phillips PCB (2009). Semiparametric
cointegrating rank selection. Econometrics Journal ,
*12*(s1), pp. S83-S104.
- Gonzalo J and Pitarakis J (1998). Specification via
model selection in vector error correction models.
Economics Letters, *60*(3), pp. 321 - 328. ISSN
0165-1765,
- Kapetanios G (2004). The Asymptotic Distribution Of The
Cointegration Rank Estimator Under The Akaike Information
Criterion. Econometric Theory, *20*(04), pp. 735-742.
- Wang Z and Bessler DA (2005). A Monte Carlo Study On
The Selection Of Cointegrating Rank Using Information
Criteria. Econometric Theory, *21*(03), pp. 593-620.
VECM
for estimating a VECM.
rank.test
(or ca.jo
in
package data(barry)
#
rk_sel <- rank.select(barry)
rk_sel
summary(rk_sel)
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