This dissertation focuses on the stochastic modelling of outstanding liabilities in non-life insurance, using Bayesian Statistics. Credible intervals and various statistical estimates can then be derived, whereas this is not the case with the numerical methods commonly used in the industry, such as the Chain Ladder, which only give point estimates. We ignore the claim numbers and concentrate on...

Predictive models play a key role for inference and decision making in crowdsourcing. We present methods that can be used to guide the collection of data for enhancing the competency of such predictive models while using the models to provide a base crowdsourcing service. We focus on the challenge of ideally balancing the goals of collecting data over time for learning and for improving task pe...

This work concerns a refinement of a suboptimal dual controller for discrete time systems with stochastic parameters. The dual property means that the control signal is chosen so that estimation of the model parameters and regulation of the output signals are optimally balanced. The control signal is computed in such a way so as to minimize the variance of output around a reference value one st...

The article presents three spreadsheet models, which integrate Monte Carlo approach with other decision support techniques, namely: forecasting methods, queuing theory and optimization. The authors indicate the most important reasons to introduce Monte Carlo approach into teaching process of simulation and spreadsheet engineering to undergraduate and graduate business students. The article conc...

We attempt to provide insights into how heterogeneity has been and can be addressed in choice modeling. In doing so, we deal with three topics: Models of heterogeneity, Methods of estimation and Substantive issues. In describing models we focus on discrete versus continuous representations of heterogeneity. With respect to estimation we contrast Markov Chain Monte Carlo methods and (simulated) ...

background: monte carlo and experimental relative dose determination in a water phantom, due to a high dose rate (hdr) 192ir source is presented for real energy spectrum and monochromatic at 356 kev. materials and methods: the dose distribution has been calculated around the 192ir located in the center of 30 cm ×30 cm ×30 cm water phantom using mcnp4c code by monte carlo method. relative dose v...

It is a pleasure to present this discussion of Chopin and Jacob (2010), which has been influenced by reading in parallel the recent paper by Chopin, Lelièvre and Stoltz (2010). This gives more detail on free-energy biasing, and applies it in the context of Markov chain Monte Carlo, and is also illustrated by applications to mixture modelling. My discussion focuses on the general ideas of free e...

In this paper the authors propose an integrated consideration set-brand choice model that is capable of accounting for the heterogeneity in consideration set and in the parameters of the brand choice model. The model is estimated by an approximation free Markov chain Monte Carlo sampling procedure and is applied to a scanner panel data. The main findings are: ignoring consideration set heteroge...

BACKGROUND Post-therapy SPECT/CT imaging of 90Y microspheres delivered to hepatic malignancies is difficult, owing to the continuous, high-energy Bremsstrahlung spectrum emitted by 90Y. This study aimed to evaluate the utility of a commercially available software package (HybridRecon, Hermes Medical Solutions AB) which incorporates full Monte Carlo collimator modelling. Analysis of image qualit...

one of the new methods for electrical powering of the bridge health monitoring systems is applying energy harvesting systems using bridge vibration. in this method, the piezoelectric material is employed for converting mechanical energy into electrical energy. the advantage of this method is based on not implementing the battery charging system. in previous research, some studies have been done...