Forecast numeric time series data with R's auto.arima algorithm.
npx skills add https://github.com/zachmayer/skills --skill forecast-zachmayer
Please help me install this Agent Skill. Skill: forecast Source: https://github.com/zachmayer/skills/tree/main/.claude/skills/forecast Command: npx skills add https://github.com/zachmayer/skills --skill forecast-zachmayer
This skill automates the complex process of statistical time series forecasting, allowing users to generate accurate predictions and confidence intervals without manual R programming.
Use the forecast skill to analyze the time series data in sales_data.csv with a monthly frequency and a 12-month horizon.
High-intent search queries and answers about installing and using this skill.
This skill predicts future trends from CSV-based time series data using R's auto.arima algorithm, automatically selecting the best model parameters to generate point predictions and confidence intervals without manual R programming.
Yes, this skill provides uncertainty quantification by generating full probability distributions and confidence intervals alongside point forecasts to support decision-making under uncertainty using R's auto.arima algorithm.
Yes, you need the R forecast package installed to execute the statistical auto.arima modeling, generate visual outputs, and simulate potential outcomes for your time series data.
You project future sales by loading historical monthly CSV data into this skill and specifying a monthly frequency with a 12-month horizon, allowing the automated ARIMA modeling to handle trend projection and seasonal analysis.
Using a skill that applies R's auto.arima algorithm automates statistical time series forecasting for seasonal analysis by automatically identifying optimal parameters to project seasonal trends and simulate potential timeline outcomes.
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