Importance Sampling and Stratification for Copula Models

An importance sampling approach for sampling from copula models is introduced. The proposed algorithm improves Monte Carlo estimators when the functional of interest depends mainly on the behaviour of the underlying random vector when at least one of its components is large. Such problems often arise from dependence models in finance and insurance. The importance sampling framework we propose is particularly easy to implement for Archimedean copulas. We also show how the proposal distribution of our algorithm can be optimized by making a connection with stratified sampling. In a case study inspired by a typical insurance application, we obtain variance reduction factors sometimes larger than 1000 in comparison to standard Monte Carlo estimators when both importance sampling and quasi-Monte Carlo methods are used.NSERC, Grant 238959 NSERC, Grant 501

Do decision support systems influence variation in prescription?

<p>Abstract</p> <p>Background</p> <p>Translating scientific evidence into daily practice is problematic. All kinds of intervention strategies, using educational and/or directive strategies, aimed at modifying behavior, have evolved, but have been found only partially successful. In this article the focus is on (computerized) decision support systems (DSSs). DSSs intervene in physicians' daily routine, as opposed to interventions that aim at influencing knowledge in order to change behavior. We examined whether general practitioners (GPs) are prescribing in accordance with the advice given by the DSS and whether there is less variation in prescription when the DSS is used.</p> <p>Methods</p> <p>Data were used from the Second Dutch National Survey of General Practice (DNSGP2), collected in 2001. A total of 82 diagnoses, 749811 contacts, 133 physicians, and 85 practices was included in the analyses. GPs using the DSS daily were compared to GPs who do not use the DSS. Multilevel analyses were used to analyse the data. Two outcome measures were chosen: whether prescription was in accordance with the advice of the DSS or not, and a measure of concentration, the Herfindahl-Hirschman Index (HHI).</p> <p>Results</p> <p>GPs who use the DSS daily prescribe more according to the advice given in the DSS than GPs who do not use the DSS. Contradictory to our expectation there was no significant difference between the HHIs for both groups: variation in prescription was comparable.</p> <p>Conclusion</p> <p>We studied the use of a DSS for drug prescribing in general practice in the Netherlands. The DSS is based on guidelines developed by the Dutch College of General Practitioners and implemented in the Electronic Medical Systems of the GPs. GPs using the DSS more often prescribe in accordance with the advice given in the DSS compared to GPs not using the DSS. This finding, however, did not mean that variation is lower; variation is the same for GPs using and for GPs not using a DSS. Implications of the study are that DSSs can be used to implement guidelines, but that it should not be expected that variation is limited.</p

Assessing the transferability of common top-down and bottom-up coarse-grained molecular models for molecular mixtures

The performance of three methods for developing new coarse-grained models for molecular simulation is critically assessed. Two bottom-up approaches are employed: iterative Boltzmann inversion (IBI) and the multiscale coarse-graining method (MS-CG), using an atomistic n-octane-benzene reference system. Results are compared to a top-down coarse-graining approach employing the SAFT-γ Mie equation of state. The performance of each methodology is assessed against the twin criteria of local structure prediction and accurate free energy representation. In addition, the transferability of the generated potentials is compared across state points. We examine the extent to which the IBI methodology can be improved by using a multi-reference approach (MS-IBI), and demonstrate how a pressure correction can be employed to improve the results for the MS-CG approach. Additionally, we look at the effect of including angle-terms in the SAFT model. Finally, we discuss in detail the strengths and weaknesses of each method and suggest possible ways forward for coarse-graining, which may eventually address the problems of structure prediction, thermodynamic consistency and improved transferability within a single model