Displaying 11 results from an estimated 11 matches for "varselect".
2011 Oct 18
0
how to use VARselect with missing values - beginner's question
... NA 1.82 -0.98 2.60 54.75
[11,] 29.91 NA 2.85 -2.01 2.61 62.51
[12,] 30.01 -4.18 0.84 0.01 0.96 52.41
[13,] 29.35 -4.06 0.92 -0.08 2.97 45.33
[14,] 29.43 -3.40 1.39 -0.54 4.02 55.15
[15,] 28.92 -3.34 1.12 -0.23 6.29 56.86
> VARselect(dadosvar,lag.max=8,type="both")
Error in VARselect(dadosvar, lag.max = 8, type = "both") :
NAs in y.
When I tried VARselect it won't work because there are missing values. Is there a way around this problem?
Thanks in advance for any help.
Kind regards,
Iara
[[altern...
2017 Nov 21
2
help
I am working on Johansen cointegration test, using urca and var package.
in the selection of var, I have got following results.
>VARselect(newd, lag.max = 10,type = "none")
$selection
AIC(n) HQ(n) SC(n) FPE(n)
6 6 6 5
$criteria
1 2 3 4
5 6 7 8 9
AIC(n) -3.818646e+01 -3.864064e+01 -3.833435e+01 -4.089169e+01
NaN -Inf -Inf -Inf -Inf
HQ...
2011 Nov 06
1
VAR and VECM in multivariate time series
...el.
I have a few questions:
1. I used acf and pacf plot and find my variables are nonstationary. But in
adf.test() and pp.test(), the data are stationary. why?
2.I use VAR to get a model. y is the matrix of data set and I have made a
once difference of it to make it stationary.
library(tsDyn)
VARselect(y,lag.max=20,type="const",season = NULL, exogen = NULL)
y1=VAR(y, p = 16, type = c("const"),
season = NULL, exogen = NULL, lag.max = NULL,ic = c("AIC"))
summary(y1)
plot(y1)
How can I get estimation of AIC in this model?
3. I also get a VECM model
v1=VECM(y, lag=16,...
2017 Nov 21
2
help
...xcuse my brevity.
>
> On November 21, 2017 12:48:08 AM PST, yadav neog <yadavneog at gmail.com>
> wrote:
> >I am working on Johansen cointegration test, using urca and var
> >package.
> >in the selection of var, I have got following results.
> >
> >>VARselect(newd, lag.max = 10,type = "none")
> >
> >$selection
> >AIC(n) HQ(n) SC(n) FPE(n)
> > 6 6 6 5
> >
> >$criteria
> > 1 2 3 4
> > 5 6 7 8 9
> >AIC(n) -3...
2017 Nov 21
0
help
...ette)
--
Sent from my phone. Please excuse my brevity.
On November 21, 2017 12:48:08 AM PST, yadav neog <yadavneog at gmail.com> wrote:
>I am working on Johansen cointegration test, using urca and var
>package.
>in the selection of var, I have got following results.
>
>>VARselect(newd, lag.max = 10,type = "none")
>
>$selection
>AIC(n) HQ(n) SC(n) FPE(n)
> 6 6 6 5
>
>$criteria
> 1 2 3 4
> 5 6 7 8 9
>AIC(n) -3.818646e+01 -3.864064e+01 -3.833435e+01 -4.08...
2010 Aug 23
2
Fitting VAR and doing Johansen's cointegration test in R
Hi,
Could someone please tell me the R codes for fitting VAR(p) (Vector
Auto Regressive) models and doing the Johansen?s cointegration tests.
TIA
Aditya
2012 Dec 05
0
Problem in summary of var results
...aset
cn.chf us.chf
2005-07-01 -1.18656633 -1.18656633
2005-07-04 -0.48835920 -0.48835920
2005-07-05 -0.01534272 -0.01534272
2005-07-06 0.08825279 0.08825279
2005-07-07 0.34223563 0.34223563
2005-07-08 -0.05776229 -0.05776229
commands which I am usings are
1) lag.var <- VARselect(data1, 10, type="both")$selection["AIC(n)"]
2) reg1 <- VAR(data1, p=lag.var)
but when I am saying summary(reg1)
and I am getting same error for irfs as well.
Its's giving me and error
Error in merge(lhs, rhs, all = FALSE) :
error in evaluating the argument 'y'...
2012 Nov 21
0
Question about VAR (Vector Autoregression) in differences.
...43728, 0.694629910826878,
0.654572164624051), .Dim = c(40L, 2L), .Dimnames = list(NULL,
c("a", "b")))
I have used the "usual" techniques to show that both of the series are I(1), (integrated of order 1) AND that there is no co-integration. In addition I used the VARselect program to estimate the number of lags.
To estimate the relationship between these variables the standard recipe (as far as I know) is to take first differences of the individual series and apply the VAR program to the new bivariate difference series.
The VAR program seems to derive a reasonable...
2012 Oct 22
0
"Vars" package: impulse response function
...ock but what is the value of this
shock? If for example I have to assess the response on 10% increase of sp
variable what should I do with these results?
Thanks a lot,
Marion
> #make a data frame
> vardat3<-data.frame(gdp,unemp,sp)
> #select the number of lags: const
> infocrit<-VARselect(vardat3,lag.max=20,type="const")
> infocrit
$selection
AIC(n) HQ(n) SC(n) FPE(n)
20 2 1 2
$criteria
1 2 3 4
AIC(n) -1.862833e+01 -1.880996e+01 -1.868877e+01 -1.863180e+01
HQ(n) -1.849392e+01 -1.857475e+01 -1.835275e+01 -1.819497e+01
SC(n) -1.829502e+01 -1.822667e+01 -1.785550e+01 -1.7...
2008 Jul 02
2
Optimal lag selection in Granger Causality tests
Dear R Users,
Can someone point me to a R package which will help me optimally choose a
lag for Granger Causality testing ?
Many thanks in advance,
Tolga
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2010 Aug 24
0
mlm for within subject design
...2*A[i-1,1]-0.2*A[i-1,3]+rnorm(1),
0.9+0.2*i+A[i-1,3]+0.1*A[i-1,1]+0.15*A[i-1,2]+rnorm(1)
)
}
(a.ct <- ur.df(A[,"a"],type="trend"))
(b.ct <- ur.df(A[,"b"],type="trend"))
(c.ct <- ur.df(A[,"c"],type="trend"))
VARselect(A,type="both")
var.p1 <- VAR(A,1,type="both")
summary(var.p1)
jo <- ca.jo(A)
summary(jo)
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