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.
- 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.
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.
Number of participants: minimum 5, maximum 10.
Length: The course takes one half-day, from 09:00 to 13:00 with 2 breaks.