[R] What is the CADF test criterion="BIC" report?
p99323005 at ntu.edu.tw
p99323005 at ntu.edu.tw
Tue Nov 15 07:34:50 CET 2011
Hello Bernhard:
Thank you for your kindly help. Actually, I have tried to read the
source code, but I can not understand it clearly. But with your
recommendation, I do think you are right.
I guess, when I use the criterion of "BIC" in CADFtest, I set the
max.lag.y=14. It seems to reduce the sample size. Although "BIC"
choose the optimal augmented lag=1, but it seems not to use the whole
sample to re-calculate the ADF-statistics.
If it is true, I think after choosing the optimal augmentd part with
"BIC", I should run the CADFtest again to avoid the misunderstanding.
Thank you again.
Best,
Paul
引述 "Pfaff, Bernhard Dr." <Bernhard_Pfaff at fra.invesco.com>:
> Hello Paul,
>
> just a guess: different sample sizes! In your first call, the sample
> is shorter than in your second. Hence, you can test this, if you
> curtail your data set in your second call and then you should obtain
> the same result, i.e.:
>
>> library(vars)
>> data(Canada)
>> test <- summary(CADFtest(Canada[-c(1:13), 1], max.lag.y = 1))
>> test
> Augmented DF test
> ADF test
> t-test statistic: -1.389086
> p-value: 0.855681
> Max lag of the diff. dependent variable: 1.000000
>
> Call:
> dynlm(formula = formula(model), start = obs.1, end = obs.T)
>
> Residuals:
> Min 1Q Median 3Q Max
> -0.79726 -0.20587 -0.03332 0.23840 0.70460
>
> Coefficients:
> Estimate Std. Error t value Pr(>|t|)
> (Intercept) 24.471789 17.521147 1.397 0.167
> trnd 0.009959 0.006941 1.435 0.156
> L(y, 1) -0.026068 0.018767 -1.389 0.856
> L(d(y), 1) 0.615983 0.092632 6.650 7.18e-09 ***
> ---
> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
>
> Residual standard error: 0.3533 on 65 degrees of freedom
> Multiple R-squared: 0.413, Adjusted R-squared: 0.3859
> F-statistic: NA on NA and NA DF, p-value: NA
>
> Though, I am not the package maintainer who could provide you with
> more insights, but the source code itself.
>
> Best,
> Bernhard
>
>
>
> -----Ursprüngliche Nachricht-----
> Von: r-help-bounces at r-project.org
> [mailto:r-help-bounces at r-project.org] Im Auftrag von
> p99323005 at ntu.edu.tw
> Gesendet: Montag, 14. November 2011 04:35
> An: r-help at r-project.org
> Betreff: [R] What is the CADF test criterion="BIC" report?
>
> Hello:
> I am a rookie in using R. When I used the unit root test in
> "CADFtest", I got the different t-test statistics between using
> criterion="BIC" and no using criterion. But when I checked the
> result with eviews, I find out that no using criterion is correct.
> Why after using criterion="BIC", I got the different result?
>
>
> Paul
>
>
>> data(Canada)
>
>> ADFt <- CADFtest(Canada[,1], max.lag.y = 14, criterion="BIC")
>
>> summary(ADFt)
> Augmented DF test
> ADF test
> t-test statistic: -1.389086
> p-value: 0.855681
> Max lag of the diff. dependent variable: 1.000000
>
> Call:
> dynlm(formula = formula(model), start = obs.1, end = obs.T)
>
> Residuals:
> Min 1Q Median 3Q Max
> -0.79726 -0.20587 -0.03332 0.23840 0.70460
>
> Coefficients:
> Estimate Std. Error t value Pr(>|t|)
> (Intercept) 24.342321 17.435476 1.396 0.167
> trnd 0.009959 0.006941 1.435 0.156
> L(y, 1) -0.026068 0.018767 -1.389 0.856
> L(d(y), 1) 0.615983 0.092632 6.650 7.18e-09 ***
> ---
> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
>
> Residual standard error: 0.3533 on 65 degrees of freedom
> Multiple R-squared: 0.413, Adjusted R-squared: 0.3859
> F-statistic: NA on NA and NA DF, p-value: NA
>
>> ADFt1 <- CADFtest(Canada[,1], max.lag.y =1)
>
>> summary(ADFt1)
> Augmented DF test
> ADF test
> t-test statistic: -2.7285715
> p-value: 0.2282588
> Max lag of the diff. dependent variable: 1.0000000
>
> Call:
> dynlm(formula = formula(model), start = obs.1, end = obs.T)
>
> Residuals:
> Min 1Q Median 3Q Max
> -0.84769 -0.24745 -0.02081 0.24187 0.82344
>
> Coefficients:
> Estimate Std. Error t value Pr(>|t|)
> (Intercept) 47.661910 17.439021 2.733 0.00776 **
> trnd 0.019217 0.007005 2.743 0.00754 **
> L(y, 1) -0.051256 0.018785 -2.729 0.22826
> L(d(y), 1) 0.753011 0.075724 9.944 1.61e-15 ***
> ---
> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
>
> Residual standard error: 0.3937 on 78 degrees of freedom
> Multiple R-squared: 0.5674, Adjusted R-squared: 0.5508
> F-statistic: NA on NA and NA DF, p-value: NA
>
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