Project

Learning R and building a package in R: a case study on photosynthesis curves using non-linear mixed-effects models

In this MSc-thesis project you can acquaint yourself with R, by studying the topic of photosynthesis curves. Repeated measurements on photosynthesis activity per leaf are obtained, rendering correlated observations per leaf. Non-linear regression models ignore the repeated measurements structure of the data. For that reason, it is better to use non-linear mixed effects models. The final goal is to build a package in R for fitting specific non-linear mixed-effects models.

Learning R and building a package in R: a case study on photosynthesis curves using non-linear mixed-effects models

(Project in collaboration with ‘gewasfysiologie en –modellering’ & Horticultural Production Chains)

In this MSc-thesis project you can acquaint yourself with R, by studying the topic of photosynthesis curves. Repeated measurements on photosynthesis activity per leaf are obtained, rendering correlated observations per leaf. Non-linear regression models ignore the repeated measurements structure of the data. For that reason, it is better to use non-linear mixed effects models. The final goal is to build a package in R for fitting specific non-linear mixed-effects models.

Description

Nowadays, R is an immensely popular statistical program, that is increasingly used by many researchers in many fields of application. It is a programming language, that allows you to build your own package and distribute it worldwide!

In this MSc-thesis project you can acquaint yourself with R, by studying the topic of photosynthesis curves. The photosynthesis activity of leaves is measured as a function of e.g. light intensity, but also CO2 levels. Repeated measurements on photosynthesis activity per leaf are obtained, rendering correlated observations per leaf. Non-linear regression models may be used to model the relationship between photosynthesis and (e.g.) CO2. However, these models ignore the repeated measurements structure of the data. For that reason, it is better to use non-linear mixed effects models. These models may be fitted in R using the nlme or lme4 package. The final goal is to build a package in R for fitting specific non-linear mixed-effects models.

Aim of the MSc project

During the MSc thesis, attention will be focussed on:

-       Getting acquainted with R

-       Getting acquainted with building a package in R

-       Getting acquainted with different non-linear mixed-effects models for analysing photosynthesis curves

-       Building an R-package for a limited number of (mixed) non-linear models for the analysis of photosynthesis curves

Key words

R, R-package, photosynthesis, non-linear mixed effects models