We discuss the estimation of derivatives of a performance measure using the likelihood ratio method in simulations of highly reliable Markovian systems. We compare the difficulties of estimating the performance measure and of estimating its partial derivatives with respect to component failure rates as the component failure rates tend to 0 and the component repair rates remain fixed. We first c...

In this paper, we discuss the problem of constructing designs in order to maximize the accuracy 9 of nonparametric curve estimation in the possible presence of heteroscedastic errors. Our approach is to exploit the 3exibility of wavelet approximations to approximate the unknown response 11 curve by its wavelet expansion thereby eliminating the mathematical di5culty associated with the unknown s...

The bias-variance decomposition of error provides useful insights into the error performance of a classifier as it is applied to different types of learning task. Most notably, it has been used to explain the extraordinary effectiveness of ensemble learning techniques. It is important that the research community have effective tools for assessing such explanations. To this end, techniques have ...

Suppose we observe an invertible linear process with independent mean-zero innovations and with coefficients depending on a finitedimensional parameter, and we want to estimate the expectation of some function under the stationary distribution of the process. The usual estimator would be the empirical estimator. It can be improved using the fact that the innovations are centered. We construct a...

A new generalized forced quantitative randomized response (GFQRR) model for estimating the population total of a sensitive variable is proposed and studied under a unified setup. The bias and variance expressions are derived under unequal probability sampling design. It is shown that the models due to Eichhorn and Hayre (1983), Bar-Lev, Bobovitch, and Boukai (2004), Liu and Chow (1976a, 1976b),...

In this study we compare revealed and stated-preference approaches to value traits of cattle in Kenya. The premise is that much can be learnt about non-market values of indigenous animal genetic resources (AnGRs) from the use of multi-attribute stated-preference methods, if these compare well with revealed-preference results. The objective is to investigate the performance of choice experiments...

Dissipation and flux-variance methods, derived from the turbulent kinetic energy and temperature variance budget equations in conjunction with Monin-Obukov similarity theory, were used to estimate surface fluxes of momentum and sensible heat. To examine the performance of these two methods, direct eddy correlation measurements were carried out above a nonuniform grass-covered forest clearing in...

Estimating option sensitivities is another quite important task in financial mathematics. In this paper, we improve the estimate of ∆ value for a vanilla European option by a robust stochastic algorithm based on quasi Monte Carlo methods and the antithetic variance reduction technique. In comparison to existing the naive Monte Carlo methods, we can improve accurate significantly by implementing...