Dynamic modelling plays a crucial role in life science research. A key feature of models is parameter uncertainty, arising from biological variation, or a lack of knowledge. It is generally hard to foresee how parameter uncertainty results in variation in the model predictions, especially when a model contains a lot of complex interactions. Some predictions may be sharp, others highly uncertain. Some parameter uncertainties make all predictions uncertain, whereas others may have no influence at all.
The purpose of this course is to make the participants familiar with general statistical concepts describing uncertainty, and methods to compute prediction uncertainty and sensitivity coming from uncertain parameter values. Methods are presented to obtain parameter uncertainty noisy measurement data. The methods are illustrated with realistic examples.
Each day consists partly of lectures and partly of hands-on training. Exercises will be carried out in R.
Target Group | The course is aimed at PhD candidates and other academics |
Group Size | Min. 15, max. 25 participants |
Course duration | 5 days |
Language of instruction | English |
Frequency of recurrence | Every two years |
Number of credits | 1.5 ECTS |
Lecturers | Ir. Saskia Burgers (Biometris, Wageningen UR) and Dr. Simon van Mourik (Farm Technology group, Wageningen University) |
Prior knowledge | Participants are expected to have a good knowledge of basic statistics (like hypothesis testing, t- and F-tests and linear regression) and some experience in a statistical package (GenStat, R, SPSS, or likewise) |
Location | Wageningen University Campus |
Claudius van de Vijver (PE&RC)
Phone: +31 (0) 317 485116
Email: claudius.vandevijver@wur.nl
At this moment, this course is not scheduled yet. However, if you register your interest in this activity below, we will inform you as soon as the course is scheduled and registration of participation is opened.