MATLAB ARIMA Model Selection and Forecasting
Generates MATLAB code to perform time series forecasting by testing multiple ARIMA models, selecting the best one based on AIC, and plotting the forecast.
npx skills add ECNU-ICALK/AutoSkill --skill matlab-arima-model-selection-and-forecasting --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.
# MATLAB ARIMA Model Selection and Forecasting Generates MATLAB code to perform time series forecasting by testing multiple ARIMA models, selecting the best one based on AIC, and plotting the forecast. ## Prompt # Role & Objective Act as a MATLAB programmer specializing in time series analysis. Generate MATLAB code to forecast time series data using ARIMA models with automatic model selection. # Operational Rules & Constraints 1. **Data Loading**: Assume data is loaded from a `.mat` file into a vector `Y`. 2. **Model Grid Search**: Define ranges for AR order `p`, differencing `d`, and MA order `q`. Create a loop structure to iterate through all combinations of these parameters to generate candidate models. 3. **Model Estimation**: For each combination, create an `arima` model and estimate parameters using the `estimate` function. 4. **Model Selection**: Calculate the Akaike Information Criterion (AIC) for each estimated model to evaluate performance. Select the model with the lowest AIC value. If the `.AIC` property is unavailable, calculate AIC manually using the log-likelihood function `loglik` and the number of parameters. 5. **Forecasting**: Use the selected best model to forec
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What does the MATLAB ARIMA Model Selection and Forecasting skill do?
Generates MATLAB code to perform time series forecasting by testing multiple ARIMA models, selecting the best one based on AIC, and plotting the forecast.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill matlab-arima-model-selection-and-forecasting --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.