Research Reports from the Department of Operations

Document Type

Report

Publication Date

12-1-1984

Abstract

Current stochastic dominance algorithms use step functions to approximate the cumulative distributions of the alternatives even when the underlying random variables are known to be continuous. Since stochastic dominance tests require repeated integration of the cumulative distribution functions, a compounding of errors may result from this approximation. This article introduces a new stochastic dominance algorithm that approximates the cumulative distribution function by piecewise linear approximations. Comparisons between the new and old algorithms are performed for normally distributed alternatives.

Keywords

Stochastic processes, Operations research, Algorithms, Probabilities

Publication Title

Technical Memorandums from the Department of Operations, School of Management, Case Western Reserve University

Issue

Technical memorandum no. 556

Rights

This work is in the public domain and may be freely downloaded for personal or academic use

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