how to extract p value for adf test in r

To extract the p-value from an ADF (Augmented Dickey-Fuller) test in R, you can use the adf.test() function from the tseries package or the ur.df() function from the urca package. Both functions provide the p-value as part of their output.

Here's an example of how to use the adf.test() function:

main.r
# Load the tseries package
library(tseries)

# Perform ADF test
result <- adf.test(your_data)

# Extract the p-value
p_value <- result$p.value

# Print the p-value
print(p_value)
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And here's an example with the ur.df() function:

main.r
# Load the urca package
library(urca)

# Perform ADF test
result <- ur.df(your_data)

# Extract the p-value
p_value <- summary(result)$teststatistic[1, "Pr(>|t|)"]

# Print the p-value
print(p_value)
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Make sure to replace your_data with your actual data.

The p-value represents the probability of observing a test statistic as extreme as the one calculated from the sample data if the null hypothesis (usually the presence of a unit root) is true. Smaller p-values indicate stronger evidence against the null hypothesis.