Space-time modelling for trend estimation of natural resources
Nicole Augustin (University of Bath)
Friday 11th January, 2013 15:00-16:00 Maths 325
We present two applications of the use of Generalized Additive Mixed Models (GAMMs) with a space time interaction represented via a tensor product of different basis functions most suitable for the dimensions of space and time. The space-time smoother allows separate smoothing parameters and penalties for the space and time dimensions and hence avoids the need to make arbitrary or ad hoc choices about the relative scaling of space and time.
The first application is for fisheries stock management. We model catch data from the blue ling fishery off the northwest coast of Scotland, using GAMMs with a space time interaction represented via a tensor product of a soap film smooth of space with a penalized regression spline of time. The use of soap film smoothers avoids imposing correspondences between spatially adjacent areas that are in fact separated by the stock boundary.
The second application is for forest health monitoring. We use a GAMM to model defoliation of beech trees in Baden-W\"urttemberg. The temporal trend of defoliation differs between areas because of site characteristics and pollution levels, making it necessary to allow for space-time interaction in the model.
This is joint work with Stefan Meining, Klaus von Wilpert, Verena Trenkel, Pascal Lorance and Simon Wood.