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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