A probabilistic forecasting method to predict thunderstorms in the European Eastern Alps is developed. A statistical model links lightning occurrence from the ground-based ALDIS detection network to a large set of direct and derived variables from a numerical weather prediction (NWP) system. The...

P(enalized)-splines and fractional polynomials (FPs) have emerged as powerful smoothing techniques with increasing popularity in several fields of applied research. Both approaches provide considerable flexibility, but only limited comparative evaluations of the performance and properties of the...

Although building operating charges have turned out to be a major determinant of profitability for real estate investments, there is a noticeable lack of reports or studies that analyze these costs with state-of-the-art statistical techniques. Specifically, past studies usually assume linear...

Bayesian methods have become increasingly popular in the past two decades. With the constant rise of computational power even very complex models can be estimated on virtually any modern computer. Moreover, interest has shifted from conditional mean models to probabilistic distributional models...

Inverse problems can be described as functional equations where the value of the function is known or easily estimable but the argument is unknown. Many problems in econometrics can be stated in the form of inverse problems where the argument itself is a function. For example, consider a...

Often researchers find parametric models restrictive and sensitive to deviations from the parametric specifications; semi-nonparametric models are more flexible and robust, but lead to other complications such as introducing infinite-dimensional parameter spaces that may not be compact and the...

Economists who use survey or administrative data for inferences regarding a population may want to combine information obtained from two or more samples drawn from the population. This is the case if there is no single sample that contains all relevant variables. A special case occurs if...

This chapter reviews recent advances in nonparametric and semiparametric estimation, with an emphasis on applicability to empirical research and on resolving issues that arise in implementation. It considers techniques for estimating densities, conditional mean functions, derivatives of...