How to extract p value from ca.po function in R? - r

Question

I want to get the p-value of both ca.po models. Can someone show me how?
at?
library(data.table)
library(urca)
dt_xy = as.data.table(timeSeries::LPP2005REC[, 2:3])
res = urca::ca.po(dt_xy, type = "Pz", demean = demean, lag = "short")
summary(res)
And the results. I marked the p-values I need in the result.
Model 1 p-value = 0.9841
Model 2 p-value = 0.1363
########################################
# Phillips and Ouliaris Unit Root Test #
########################################
Test of type Pz
detrending of series with constant and linear trend
Response SPI :
Call:
lm(formula = SPI ~ zr + trd)
Residuals:
Min 1Q Median 3Q Max
-0.036601 -0.003494 0.000243 0.004139 0.024975
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 9.702e-04 7.954e-04 1.220 0.223
zrSPI -1.185e-02 5.227e-02 -0.227 0.821
zrSII -3.037e-02 1.374e-01 -0.221 0.825
trd -6.961e-07 3.657e-06 -0.190 0.849
Residual standard error: 0.007675 on 372 degrees of freedom
Multiple R-squared: 0.0004236, Adjusted R-squared: -0.007637
F-statistic: 0.05255 on 3 and 372 DF, p-value: 0.9841 **<--- I need this p.value**
Response SII :
Call:
lm(formula = SII ~ zr + trd)
Residuals:
Min 1Q Median 3Q Max
-0.0096931 -0.0018105 -0.0002734 0.0017166 0.0115427
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -7.598e-05 3.012e-04 -0.252 0.8010
zrSPI -1.068e-02 1.979e-02 -0.540 0.5897
zrSII -9.574e-02 5.201e-02 -1.841 0.0664 .
trd 1.891e-06 1.385e-06 1.365 0.1730
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.002906 on 372 degrees of freedom
Multiple R-squared: 0.01476, Adjusted R-squared: 0.006813
F-statistic: 1.858 on 3 and 372 DF, p-value: 0.1363 **<--- I need this p.value**
Value of test-statistic is: 857.4274
Critical values of Pz are:
10pct 5pct 1pct
critical values 71.9586 81.3812 102.0167

Answer 1

You have to dig into the res object to see its attributes and what's available there.
attributes(reg)
...
#>
#> $testreg
#> Response SPI :
#>
#> Call:
#> lm(formula = SPI ~ zr + trd)
#>
...
A long list of objects is returned, but we can see what is looking like the summary of lm being called under testreg, which we can see is one of the attributes of res. We can also access attributes of res using attr(res, "name"), so let's look at the components of testreg.
names(attributes(res))
#> [1] "z" "type" "model" "lag" "cval" "res"
#> [7] "teststat" "testreg" "test.name" "class"
names(attr(res, "testreg"))
#> [1] "Response SPI" "Response SII"
As you noted above, you're looking for 2 separate p-values, so makes since we have two separate models. Let's retrieve these and look at what they are.
spi <- attr(res, "testreg")[["Response SPI"]]
sii <- attr(res, "testreg")[["Response SII"]]
class(spi)
#> [1] "summary.lm"
So, each of them is a summary.lm object. There's lots of documentation on how to extract p-values from lm or summary.lm objects, so let's use the method described here.
get_pval <- function(summary_lm) {
pf(
summary_lm$fstatistic[1L],
summary_lm$fstatistic[2L],
summary_lm$fstatistic[3L],
lower.tail = FALSE
)
}
get_pval(spi)
#> value
#> 0.9840898
get_pval(sii)
#> value
#> 0.1363474
And there you go, those are the two p-values you were interested in!