Often researchers find parametric models restrictive and sensitive to deviations from the
parametric specifications; semi-nonparametric models are more flexible and robust, but lead …

Supplement to “A Comparative Review of Dimension Reduction Methods in Approximate
Bayesian Computation”. The supplement contains for each of the three examples a …

Explaining complex or seemingly simple machine learning models is an important practical
problem. We want to explain individual predictions from such models by learning simple …

'Optimal cutpoints' for binary classification tasks are often established by testing which
cutpoint yields the best discrimination, for example the Youden index, in a specific sample …

The co-existence of traditional docked bike-sharing and emerging dockless systems
presents new opportunities for sustainable transportation in cities all over the world, both …

Vegetation phenology controls the seasonality of many ecosystem processes, as well as
numerous biosphere-atmosphere feedbacks. Phenology is also highly sensitive to climate …

Recent work by Reiss and Ogden provides a theoretical basis for sometimes preferring
restricted maximum likelihood (REML) to generalized cross-validation (GCV) for smoothing …

To understand the current biodiversity crisis, it is crucial to determine how humans have
affected biodiversity in the past. However, the extent of human involvement in species …

Spatial statistics is a growing discipline providing important analytical techniques in a wide
range of disciplines in the natural and social sciences. In the R package GWmodel, we …

Urban vibrancy describes the attraction, diversity and accessibility of a place and exhibits
spatio-temporal variability. The relationships between urban vibrancy and land-use …