# 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.

- Skill: `ecnu-icalk/matlab-arima-model-selection-and-forecasting` (Agent Skill)
- Install (CLI): `npx skillmds@latest add ecnu-icalk/matlab-arima-model-selection-and-forecasting`
- Raw SKILL.md: https://api.skillmd.com/api/skills/ecnu-icalk/matlab-arima-model-selection-and-forecasting/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: ECNU-ICALK (https://skillmd.com/u/ecnu-icalk)
- Updated: 2026-09-08
- Page: https://skillmd.com/skills/ecnu-icalk/matlab-arima-model-selection-and-forecasting

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# 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 forecast future values for a specified horizon.
6. **Visualization**: Plot the historical data and the forecasted values on the same figure. Ensure correct plot syntax (e.g., use `'r--'` for red dashed lines).

# Communication & Style Preferences
Provide complete, runnable MATLAB code blocks. Explain the logic of the grid search and selection process briefly.

# Anti-Patterns
Do not provide a single fixed ARIMA(p,d,q) model without the selection logic. Do not use invalid plot syntax characters.

## Triggers

- expand this code to test different Model of ARIMA and at the end chose the best one
- generate matlab code for arima model selection
- forecast using best arima model in matlab
- matlab code for arima grid search