# Nonlinear regression with R

The aim of this course is to teach you how to analyse your data
if there are complicated relationships between the variables.
**Please note that we cannot go into the specific data analysis problems of your particular project.**

**Instructor:** András Aszódi.

## Topics

- How to fit a PCR curve? Univariate nonlinear regression.
- More than one independent variable? Multivariate nonlinear regression.
- The flu epidemic is coming again? Modelling periodic phenomena.
- Smoothing by fitting: LOESS, kernel smoothing methods, splines, generalized additive models.

## Prerequisites

Participants should have a good understanding of basic statistics. Our Statistics with R course helps you refresh your stats skills. Ideally, you should attend the Linear regression course before learning nonlinear regression.

Basic familiarity with R is advantageous, in particular:

- Using the R Studio environment
- How to invoke R functions, pass optional/named parameters
- Some familiarity with simple plotting commands

If you have attended our R as a programming language training then you are well equipped to take this course, but this is not a strict pre-requisite.

## Practical information

**Number of participants:** minimum 5, maximum 10.

**Length:** The course takes one half-day,
from 09:00 to 13:00 with 2 breaks.