regression and simulation-based least-squares Monte Carlo method by using put-call symmetry. The results show that, for a large …

Bayesian forecasting is a natural product of a Bayesian approach to inference. The Bayesian approach in general …. In Bayesian forecasting, one simply takes a subset of the unknown quantities to be future values of some variables of … interest. This chapter presents the principles of Bayesian forecasting, and describes recent advances in computational …

In this paper we use Monte Carlo simulation to investigate the impact of effect size heterogeneity on the results of a …

sophisticated neural network simulation techniques is explored. In all examples considered in this paper – a bimodal distribution of …

and smoother and the simulation smoother which do not rely on a linear Gaussian observation equation. Furthermore, results …

their performance in simulation experiments. This leads to a list of eight methodologic aspirations. Against their … background we criticize aspects of many simulation studies that have been used in the past to compare competing estimators for … simulation design inspired by an analysis of the (non-)invariance properties of estimators and occasionally by available higher …