Economic/calculate-methods
plugins/r-econ-data/skills/calculate-methods/SKILL.md
Methods for calculating statistics and estimates using economic data. Use when user asks to calculate or estimate quantities like percentiles, means, medians, shares, counts, or regression coefficients or regression-adjusted statistics.
testing
Updated Apr 4, 2026
$ install --global
skillsauthnpx skillsauth add Economic/epi-skills calculate-methodsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- calculate-methods
- description:
- Methods for calculating statistics and estimates using economic data. Use when user asks to calculate or estimate quantities like percentiles, means, medians, shares, counts, or regression coefficients or regression-adjusted statistics.
Moving averages and sliding windows
Often data over time is very noisy and moving averages can better extract signals. Use the R package slider for calculations over sliding windows like moving averages.
Weighted means, medians, percentiles
Use weighted.mean(vector, w = weight) for weighted means.
Use the MetricsWeighted package for weighted medians and percentiles: weighted_median(vector, w = weight) and weighted_quantile(vector, w = weight, probs = c(0.25, 0.50, 0.75)).
Percentiles with "bunched" data
When using data that is assumed to be continuous but in practice is "bunched" at discrete points -- like reported hourly wages -- it can be helpful to smooth the estimated percentiles. One technique is to take a weighted average of nearby percentiles. For example, consider using the epidatatools package averaged_median(vector, w = weight) and averaged_quantile(vector, w = weight, probs = c(0.25, 0.50, 0.75)).
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