We propose a new approach to deal with structural breaks in time series models. The key contribution is an alternative dynamic stochastic specification for the model parameters which describes potential breaks. After a break new parameter values are generated from a so-called baseline prior...

In order to study the dynamic changes in gas concentration, to reduce gas hazards, and to protect and improve mining safety, a new method is proposed to predict gas concentration. The method is based on the opposite degree algorithm. Priori and posteriori values, opposite degree computation,...

This paper puts forward kernel ridge regression as an approach for forecasting with many predictors that are related nonlinearly to the target variable. In kernel ridge regression, the observed predictor variables are mapped nonlinearly into a high-dimensional space, where estimation of the...

In the search for effective pesticide risk management tools, the design of pesticide risk indicators is nowadays receiving increasing attention as a complement to more established regulatory strategies. In the present paper, we apply some recently developed pesticide risk indices and test their...

In this article we consider the efficient estimation of the tail distribution of the maximum of correlated normal random variables. We show that the currently recommended Monte Carlo estimator has difficulties in quantifying its precision, because its sample variance estimator is an inefficient...

This paper considers a general class of stochastic dynamic choice models with discrete and continuous decision variables. This class contains a variety of models that are useful for modeling intertemporal household decisions under risk. Our examples are drawn from the field of development...

This paper points out the importance of Stochastic Dominance (SD) efficient sets being convex. We reviewclassic convexity and efficient set characterization results on SD efficiency of a given portfolio relative to adiversified set of assets and generalize them in the following aspects. First,...

In this paper we study a challenging call center operation problem. The goal of our analysis is to identify an optimal policy for allocating tasks to agents. As a first step, we discuss promising randomized policies and use stochastic approximation for finding the optimal randomized policy when...