Hi,
Please read Time series Econometrics books and you will find out that
acf and pacf are not to be used to determine whether or not a series is
stationary. The question of nonstationarity or stationarity of a series
is answered using the formal tests comprising ADF, PP, KPSS, etc.
I will let someone else (and I know that there is at least one such
expert) deal with your question on VAR and tsDyn.
Lexi
-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
On Behalf Of cloris
Sent: Sunday, November 06, 2011 5:25 PM
To: r-help at r-project.org
Subject: [R] VAR and VECM in multivariate time series
Hello to everyone!
I am working on my final year project about multivariate time series.
There are three variables in the multivariate time series model.
I have a few questions:
1. I used acf and pacf plot and find my variables are nonstationary. But
in
adf.test() and pp.test(), the data are stationary. why?
2.I use VAR to get a model. y is the matrix of data set and I have made
a once difference of it to make it stationary.
library(tsDyn)
VARselect(y,lag.max=20,type="const",season = NULL, exogen = NULL)
y1=VAR(y, p = 16, type = c("const"), season = NULL, exogen = NULL,
lag.max = NULL,ic = c("AIC"))
summary(y1)
plot(y1)
How can I get estimation of AIC in this model?
3. I also get a VECM model
v1=VECM(y, lag=16,beta=NULL, estim="ML")
what does ETC mean in the output?
and what is a number of cointegrating relationships?
I want to make forecast by VECM.
j=ca.jo(y,K=16,type='trace',season = NULL)
j.var=vec2var(j)
predict(j.var,n.ahead=80)
Is this a correct way to predict VECM in R?
Could anyone help me?
Thank you very much
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