OBJECTIVE: The purpose of this study was to identify hospital organizational characteristics consistently associated with adherence to multiple clinical practice guidelines (CPGs). We examined the relationship between organizational and patient population characteristics and adherence to three...

Diese Arbeit untersucht die Anwendung von Support Vektor Machines (SVMs) zur Vorhersage der Insolvenz von deutschen Unternehmen. Die Vorhersage basiert auf 24 finanziellen Kennzahlen, die in vier Kategorien unterteilt sind: Profitabilität, Fremdfinanzierung, Liquidität und Aktivität. SVMs...

It is well known that the bridge regression (with tuning parameter less or equal to 1) gives asymptotically unbiased estimates of the nonzero regression parameters while shrinking smaller regression parameters to zero to achieve variable selection. Despite advances in the last several decades in...

The paper analyzes factors that influence the adoption of e-learning and gives an example of how to forecast technology adoption based on a post-hoc predictive segmentation using a classification and regression tree (CART). We find strong evidence for the existence of technological...

Gene expression datasets usually have thousends of explanatory variables which are observed on only few samples. Generally most variables of a dataset have no effect and one is interested in eliminating these irrelevant variables. In order to obtain a subset of relevant variables an appropriate...

This paper investigates the earnings effects of training in the Portuguese labour market. We use the Portuguese Labour Force Survey to classify training according to multiple criteria, including providing institution, purpose, duration, and content of the training activity. First, we establish...

Accurate credit-granting decisions are crucial to the efficiency of the decentralized capital allocation mechanisms in modern market economies. Credit bureaus and many financial institutions have developed and used credit-scoring models to standardize and automate, to the extent possible, credit...

Data sets from car insurance companies often have a high-dimensional complex dependency structure. The use of classical statistical methods such as generalized linear models or Tweedie?s compound Poisson model can yield problems in this case. Christmann (2004) proposed a general approach to...

Some methods from statistical machine learning and from robust statistics have two drawbacks. Firstly, they are computer-intensive such that they can hardly be used for massive data sets, say with millions of data points. Secondly, robust and non-parametric confidence intervals for the...

Credit risk measurement and management become more important in all financial institutions in the light of the current financial crisis and the global recession. This particularly applies to most of the complex structured financing forms whose risk cannot be quantified with com-mon rating...