look at the problem of calibrating financial models, measuring the model uncertainty of a claim and choosing an optimal … uncertainty. Using the framework for market risk measures we propose axioms for new classes of model uncertainty measures. Similar … to the market risk case, we prove representation theorems for coherent and convex model uncertainty measures. Example …

, factor based bootstrap approach is proposed for inferential issues in functional coefficient models. This approach can cope … with heterogeneous error distributions and is proven to hold asymptotically. In simulation studies factor based bootstrap … inference outperforms the wild bootstrap and pairs bootstrap approach according to its size features. Regarding current account …

The application of the bootstrap to spatially correlated data has not been studied as widely as its application to time … implementing the bootstrap method. Kunsch (1989), Politis and Romano(1993, Liu and Singh(1992) have suggested bootstrapping methods …

Poisson regression in a log-linear model. The third one is a nonparametric approach based on bootstrap percentile confidence … computationally expensive and it has desirable Type I errors in most cases as well as good powers. The bootstrap-based method is the …

) estimation and by Huber Proposal 2 M-estimation. We also apply bootstrap methods to these Levene type tests and compare by …

-order selection criteria (both information theoretic based and bootstrap-based). Also, we show that for some models the performance of … the bootstrap-based criterion improves significantly by using the proposed partial-model selection searching method. Index … Terms— Model order estimation, model selection, information theoretic criteria, bootstrap 1. INTRODUCTION Several model …

management.The second chapter (Hoyle and Cameron 2003, published in Fisheries Management and Ecology) focuses on uncertainty in … the classical paradigm, by investigating the best way to estimate bootstrap confidence limits on recreational harvest and …

estimator (CME), the bootstrap and the more recently proposed hook-and-loop resampling based model selection. The advantages and …