Estimating the mean of a non-linear function of conditional expectation

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review

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Author(s)

Detail(s)

Original languageEnglish
Title of host publicationProceedings - Winter Simulation Conference
Pages1223-1236
Publication statusPublished - 2009
Externally publishedYes

Publication series

Name
ISSN (Print)0891-7736

Conference

Title2009 Winter Simulation Conference, WSC 2009
PlaceUnited States
CityAustin
Period13 - 16 December 2009

Abstract

Consider the problem of estimating the expectation of a non linear function of a conditional expectation. This function is allowed to be non-differentiable and discontinuous at a finite set of points to capture practical settings. We develop a nested simulation strategy to estimate this via simulation and identify bias and optimized mean square error allocation. We show that this mean square error converges to zero at the rate Γ-2/3, as Γ → ∞, where Γ denotes the available computational budget. We also consider combining nested simulation technique with kernel based estimation methods. We note that while the kernel based method have a better convergence rate when the underlying random process has dimensionality less than or equal to three, pure nested simulation may be preferred when this dimension is above four. ©2009 IEEE.

Citation Format(s)

Estimating the mean of a non-linear function of conditional expectation. / Hong, L. Jeff; Juneja, Sandeep.

Proceedings - Winter Simulation Conference. 2009. p. 1223-1236 5429428.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review