Unbiased Random Integration Methods with Exactness for Low Order Polynomials

When a definite integral cannot be evaluated exactly, the authors turn to computer-based methods for approximations. There are many different kinds of such procedures, but they divide roughly into two classes: deterministic and random. They explore the use of methods that combine these two approache...

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Bibliographic Details
Main Authors: Siegel,Andrew F, O'Brien,Fanny
Format: Report
Language:English
Subjects:
Approximation(Mathematics)
Component reports
Estimates
Integrals
Integration
Monte Carlo method
Numerical methods and procedures
Polynomials
Random variables
Two dimensional
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Summary:When a definite integral cannot be evaluated exactly, the authors turn to computer-based methods for approximations. There are many different kinds of such procedures, but they divide roughly into two classes: deterministic and random. They explore the use of methods that combine these two approaches, preserving the unbiasedness and error estimation advantages of random methods, but at the same time maintaining the closer approximation generally found in deterministic methods. (Author) This article is from 'Proceedings of the Conference on the Design of Experiments in Army Research Development and Testing (28th) Held at Monterey, California on 20-22 October 1982,' AD-A130 826. p351-355.