I would like to know how I can access the individual fields contained in an R object. Or, more precisely, how to get R to tell me how.
For example, if I run the following code:
dx.ct <- ur.df(dat1[,'dx'], lags=3, type='trend')
summary(dx.ct)
then I get this output:
###############################################
# Augmented Dickey-Fuller Test Unit Root Test #
###############################################
Test regression trend
Call:
lm(formula = z.diff ~ z.lag.1 + 1 + tt + z.diff.lag)
Residuals:
Min 1Q Median 3Q Max
-0.46876 -0.24506 0.02420 0.15752 0.66688
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.099231 0.561377 1.958 0.0606 .
z.lag.1 -0.239438 0.141093 -1.697 0.1012
tt -0.019831 0.007799 -2.543 0.0170 *
z.diff.lag1 -0.306326 0.193001 -1.587 0.1241
z.diff.lag2 -0.214229 0.186135 -1.151 0.2599
z.diff.lag3 -0.223433 0.179040 -1.248 0.2228
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.3131 on 27 degrees of freedom
Multiple R-squared: 0.3326, Adjusted R-squared: 0.209
F-statistic: 2.691 on 5 and 27 DF, p-value: 0.04244
Value of test-statistic is: -1.697 2.4118 3.2358
Critical values for test statistics:
1pct 5pct 10pct
tau3 -4.15 -3.50 -3.18
phi2 7.02 5.13 4.31
phi3 9.31 6.73 5.61
So, I know that I should be able to access all of the values above individually, I don't know how to point to them. Is there some way to ask R to show me how they are stored?
I am thinking along the lines of:
showobjects(summary(dx.ct))
And then it outputs
$formula
$residuals
$coefficients
etc.
and then I can do
showobjects(summary(dx.ct)$residuals)
which then outputs
$min
$1Q
$median
etc.
Thanks
Karl
Answer
As another alternative, take a look at attributes. e.g.
example(ur.df)
attributes(lc.df) #lc.df is an ur.df object created during by example.
$y
[1] 10.4831 10.4893 10.5022 10.5240 10.5329 10.5586 10.5190 10.5381
[9] 10.5422 10.5361 10.5462 10.5459 10.5552 10.5548 10.5710 10.5861
[17] 10.5864 10.5802 10.6006 10.6168 10.6275 10.6414 10.6629 10.6758
[25] 10.6881 10.7240 10.7143 10.7222 10.7156 10.6964 10.6990 10.7081
[33] 10.7142 10.7078 10.7073 10.6954 10.6910 10.6967 10.7015 10.7083
[41] 10.7127 10.6922 10.6874 10.6989 10.7224 10.7452 10.7462 10.7663
[49] 10.7633 10.7737 10.8282 10.7872 10.8015 10.8139 10.7909 10.8029
[57] 10.7868 10.7979 10.8007 10.8008 10.7991 10.7956 10.8005 10.8160
[65] 10.8260 10.8405 10.8482 10.8633 10.8633 10.8615 10.8732 10.8649
[73] 10.8793 10.8909 10.8938 10.9116 10.9202 10.9409 10.9663 10.9700
[81] 10.9808 10.9878 11.0048 11.0272 11.0420 11.0701 11.0751 11.0964
[89] 11.1069 11.1123 11.1231 11.1223 11.1303 11.1307 11.1389 11.1325
[97] 11.1261 11.1232 11.1220
$model
[1] "trend"
$lags
[1] 3
# etc.
If you don't want the full output, then names(attributes(lc.df)) returns only the, um, names.
[1] "y" "model" "lags" "cval" "res" "teststat" "testreg" "test.name" "class"