Module 4: Non-linear Regression & GAMs

Topic: Non-linear curve fitting, generalized additive models (GAMs), writing your own R functions.

Learning Objectives

Fit non-linear models with nls()
Use mgcv::gam() for flexible smooth terms
Write reusable R functions
Visualize non-linear relationships

Slides

L7 Nonlinearity (PDF)

R Code

Non-linear models.R

Data

Key Packages

library(mgcv)

Assignment

HW4: Nonlinear Regression — due Module 5 Wednesday. Submit on Canvas.

---
title: "Module 4: Non-linear Regression & GAMs"
---

::: {.week-header}
**Topic:** Non-linear curve fitting, generalized additive models (GAMs), writing your own R functions.
:::

## Learning Objectives

- Fit non-linear models with `nls()`
- Use `mgcv::gam()` for flexible smooth terms
- Write reusable R functions
- Visualize non-linear relationships

## Slides

::: {.file-list}
- [L7 Nonlinearity (PDF)](../Week%204/L7_nonlinearity.pdf)
:::

## R Code

::: {.file-list}
- [Non-linear models.R](../Week%204/Non-linear%20models.R)
:::

## Data

::: {.file-list}
- [climate.csv](../Week%204/climate.csv)
- [hemispheres.csv](../Week%204/hemispheres.csv)
:::

## Key Packages

```r
library(mgcv)
```

## Assignment

**HW4: Nonlinear Regression** — due Module 5 Wednesday. Submit on Canvas.