The paper considers nonparametric estimation of Value at Risk (VaR) and associated standard error estimation for dependent financial returns. Theoretical properties of the kernel VaR estimator are investigated in the context of dependence. The presence of dependence affects the variance of the VaR estimates and has to be taken into consideration in order to obtain adequate assessment of their v...

This paper deals with the problems of robust H2 and H∞ filtering for a class of linear continuous-time systems subject to uncertain constant parameters and both additive and state-dependent noise signals. The uncertain parameters appear affinely in the matrices of the system state-space model and are assumed to belong to a given polytope. Linear matrix inequality approaches are proposed for des...

We develop and test robust methods for design construction, for estimation and for prediction in spatial studies. The designs are robust against misspecified variance/covariance structures, and against misspecified regression responses. Robustness against contaminated error distributions is provided by the use of generalized M-estimators in the estimation and prediction procedures. The loss fun...

We consider the Generalised Normal Variance-Mean (GNVM) model in which the mixing random variable is Gamma distributed for financial return data. This model generalises the popular Variance-Gamma (VG) distribution. This GNVM model can be interpreted as the addition of noise to a (skew) VG base. In this presentation, we will not only discuss the parameter estimation of the general model, but als...

In this correspondence, a finite-horizon discrete H1 filter design with a linear quadratic (LQ) game approach is presented. The exogenous inputs composed of the “hostile” noise signals and system initial condition are assumed to be finite energy signals with unknown statistics. The design criterion is to minimize the worst possible amplification of the estimation error signals in terms of the e...

In this paper, we have studied the estimation of parameters under failure censored data using step stress partially accelerated life testing. The lifetimes of test items are assumed to follow Mukherjee-Islam distribution. The estimation of different parameters and acceleration factor are obtained by Maximum Likelihood Method. Relative absolute bias (RAB), mean squared error (MSE), relative erro...

This paper presents an effort to validate the incident duration estimation model of WAIMSS Wide Area Incident Management Support System (WAIMSS). Duration estimation model of WAIMSS predicts the incident duration based on an estimation tree which was calibrated using incident data collected in Northem Virginia. The validation process started with collection of new incident data which was conduc...