How does this skill handle weighted data in R?

It provides implementation patterns using weighted.mean and the MetricsWeighted package to ensure accurate weighted medians and quantiles in economic datasets.

Does this skill support regression analysis?

Yes, it provides guidance for calculating regression coefficients and regression-adjusted statistics specifically tailored for economic modeling.

What is the solution for bunched data points?

The skill utilizes the epidatatools package to apply averaged_median and averaged_quantile methods, which smooths data that is assumed continuous but reported at discrete points.

Can I use this for time-series analysis?

Yes, it includes specialized methods for moving averages and sliding window calculations using the R 'slider' package to extract signals from noisy temporal data.

Economic Data Statistics Methods

Name: Economic Data Statistics Methods
Author: Economic

byEconomic

0•

Ciencia de Datos y ML

Calculates advanced economic statistics and estimates using specialized R methodologies for weighted and bunched data.

This skill provides specialized guidance for performing complex economic data analysis within Claude Code, offering specific implementation patterns for calculating weighted means, medians, and percentiles. It excels at handling advanced scenarios such as smoothing 'bunched' continuous data—common in reported hourly wages—via the epidatatools package and processing noisy time-series data through moving averages with the slider package. It is an essential toolkit for researchers and data scientists who require precise, statistically sound results from raw economic datasets using the R programming language.

Características Principales

01Regression-adjusted statistics and coefficient estimation

02Weighted mean, median, and quantile calculations

030 GitHub stars

04Integration with MetricsWeighted and slider R packages

05Moving average and sliding window implementation

06Bunched data smoothing via averaged percentiles

Casos de Uso

01Estimating smoothed percentiles for data reported at discrete intervals

02Analyzing labor market surveys to find weighted median hourly wages

03Extracting signals from noisy economic time-series using moving averages

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add economic/epi-skills calculate-methods

For use in Claude.ai and ChatGPT

Características Principales

01Regression-adjusted statistics and coefficient estimation

02Weighted mean, median, and quantile calculations

030 GitHub stars

04Integration with MetricsWeighted and slider R packages

05Moving average and sliding window implementation

06Bunched data smoothing via averaged percentiles

Casos de Uso

01Estimating smoothed percentiles for data reported at discrete intervals

02Analyzing labor market surveys to find weighted median hourly wages

03Extracting signals from noisy economic time-series using moving averages

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add economic/epi-skills calculate-methods

For use in Claude.ai and ChatGPT