Now showing items 1-6 of 6
Bayesian hierarchical modelling of growth curve derivatives via sequences of quotient differences
Growth curve studies are typically conducted to evaluate differences between group or treatment-specific curves. Most analyses focus solely on the growth curves, but it has been argued that the derivative of growth curves ...
On the estimation of variance parameters in non-standard generalised linear mixed models: Application to penalised smoothing
We present a novel method for the estimation of variance parameters in generalised linear mixed models. The method has its roots in Harville (1977)'s work, but it is able to deal with models that have a precision matrix ...
Spatio-temporal adaptive penalized splines with application to Neuroscience
Data analysed here derive from experiments conducted to study neurons' activity in the visual cortex of behaving monkeys. We consider a spatio-temporal adaptive penalized spline (P-spline) approach for modelling the firing ...
Fast estimation of multidimensional adaptive P-spline models
A fast and stable algorithm for estimating multidimensional adaptive P-spline models is presented. We call it as Separation of Overlapping Penalties (SOP) as it is an extension of the Separation of Anisotropic Penalties ...
Fast algorithm for smoothing parameter selection in multidimensional P-splines
A new computational algorithm for estimating the smoothing parameters of a multidimensional penalized spline generalized model with anisotropic penalty is presented. This new proposal is based on the mixed model representation ...
Fast smoothing parameter separation in multidimensional generalized P-splines: the SAP algorithm
A new computational algorithm for estimating the smoothing parameters of a multidimensional penalized spline generalized linear model with anisotropic penalty is presented. This new proposal is based on the mixed model ...