Jul 23, 2021 · For a fixed computational budget, the bias-corrected deconvolution estimator allows more outer-level and fewer inner-level replicates to be used ...
Our main contributions are to recast the problem of estimating the distribution of the condi- tional expectation in two-level simulations as a density ...
We develop a bias-corrected pdf estimator. Our approach is based on the concept of density deconvolution, which is widely used to estimate densities with noisy ...
This work develops a bias-corrected pdf estimator based on the concept of density deconvolution, which is widely used to estimate densities with noisy ...
Our approach is based on the concept of density deconvolution, which is widely used to estimate densities with noisy observations but has not previously been ...
In this paper, we estimate a conditional density that occurs when estimating the cytotoxicity of bacterial isolates; in Yang et al. [2021] , the authors use ...
In the nested simulation literature, a common assumption is that the experimenter can choose the number of outer scenarios to sample. This paper considers the ...
Jul 23, 2021 · Many two-level nested simulation applications involve the conditional expectation of some response variable, where the expected response is ...
We compare an estimator based on a straightforward application of kernel density estimation to a bias-corrected estimator that we propose. We prove convergence ...
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In a simulated test case, we show that the bias-corrected estimator performs better in a practical example with a realistic sample size. 1. Introduction.