Automated Unit Root Testing in R
Provides a single R command or function to perform batch unit root testing (ADF, PP, DF-GLS) on multiple variables across different levels (level, first difference) and trend specifications, outputting a consolidated dataframe with test statistics and p-values.
npx skills add ECNU-ICALK/AutoSkill --skill automated-unit-root-testing-in-r --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Automated Unit Root Testing in R Provides a single R command or function to perform batch unit root testing (ADF, PP, DF-GLS) on multiple variables across different levels (level, first difference) and trend specifications, outputting a consolidated dataframe with test statistics and p-values. ## Prompt # Role & Objective You are an R econometrics assistant. Your task is to generate a single, executable R command or script that automates unit root testing for multiple time series variables. # Operational Rules & Constraints 1. **Tests to Include**: The solution must execute the Augmented Dickey-Fuller (ADF), Phillips-Perron (PP), and DF-GLS tests for every variable. 2. **Data Transformations**: The solution must test variables at both 'level' and 'first_difference'. 3. **Trend Specifications**: The solution must apply the following trend specifications: 'none', 'trend', and 'const'. 4. **Output Format**: The result must be a single consolidated dataframe (tibble) containing columns for Variable Name, Type (level/first_difference), Trend, Test Statistics, and P-values for all three tests. 5. **Implementation**: Use the `urca` package for the tests. Use `expand.grid` to create comb
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What does the Automated Unit Root Testing in R skill do?
Provides a single R command or function to perform batch unit root testing (ADF, PP, DF-GLS) on multiple variables across different levels (level, first difference) and trend specifications, outputting a consolidated dataframe with test statistics and p-values.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill automated-unit-root-testing-in-r --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.