For spline regressions, it is well known that the choice of knots is crucial for the performance
of the estimator. As a general learning framework covering the smoothing splines, learning …

Penalized splines have gained much popularity as a flexible tool for smoothing and semi‐
parametric models. Two approaches have been advocated:(1) use a B‐spline basis, equally …

We used a Bayesian hierarchical selection model to study publication bias in 1106 meta‐
analyses from the Cochrane Database of Systematic Reviews comparing treatment with …

Semiparametric regression is concerned with the flexible incorporation of non-linear
functional relationships in regression analyses. Any application area that benefits from …

It's been over a decade since the first edition of Measurement Error in Nonlinear Models
splashed onto the scene, and research in the field has certainly not cooled in the interim. In …

Computer simulations based on mathematical models have become ubiquitous across the
engineering disciplines and throughout the physical sciences. Successful use of a …

Agricultural abandonment is widespread and growing in many regions worldwide, often
because of agricultural intensification on productive lands, conservation policies, or the …

Single-index models are potentially important tools for multivariate nonparametric
regression. They generalize linear regression by replacing the linear combination α0Tx with …

INLA stands for Integrated Nested Laplace Approximations, which is a new method for fitting
a broad class of Bayesian regression models. No samples of the posterior marginal …

In this paper we propose a categorization of green space into eight different types and
quantify their impact on housing prices in the city of Aalborg using the hedonic house price …