# linear_models

> This document provides detailed guidance on linear regression models in statsmodels, including OLS, GLS, WLS, quantile regression, and specialized variants

- Source: https://doutorai.pt/en/components/skills__linear-models
- Type: Skills
- Category: Scientific
- Downloads: 0
- Site: Doutor AI (https://doutorai.pt/en) - AI tools for small businesses

An open-source community component, curated and adapted by Doutor AI.

## What it does and how to use it

A **skill** that teaches Claude Code to do scientific tasks well. It is packaged knowledge the model uses whenever it is relevant.

1. Install the skill (command above).
2. In Claude Code, describe what you need - the skill turns on by itself when the context fits.
3. No commands to memorize: you talk in plain language and the skill does the rest.

## Install (Claude Code)

```bash
mkdir -p .claude/skills/linear-models && curl -fsSL https://doutorai.pt/data/lib/skills__linear-models.md -o .claude/skills/linear-models/SKILL.md
```

Paste this command into the terminal, in your project folder, and the component installs automatically.

## Content

````
# Linear Regression Models Reference

This document provides detailed guidance on linear regression models in statsmodels, including OLS, GLS, WLS, quantile regression, and specialized variants.

## Core Model Classes

### OLS (Ordinary Least Squares)

Assumes independent, identically distributed errors (Σ=I). Best for standard regression with homoscedastic errors.

**When to use:**
- Standard regression analysis
- Errors are independent and have constant variance
- No autocorrelation or heteroscedasticity
- Most common starting point

**Basic usage:**
```python
import statsmodels.api as sm
im

- 🔒 Full content on the Pro plan (€7.99/month) -
````

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Content by Doutor AI (https://doutorai.pt/en). When quoting, please cite the source: https://doutorai.pt/en/components/skills__linear-models