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The Refining of Descriptive Sampling

Megdouda TARI, Abdelnasser Dahmani

Abstract


Descriptive sampling is one procedure that entails a full control over the input set of sample values. This method is based on a regular selection of the sample values and their random permutation. One of the limitation is that, in general
cases, it leads to biased results in simulation. This approach is also hard to implement efficiently as it needs prior
knowledge of the sample size. The paper analyses the conditions under which bias can occur and we find that the worst situation which could occur is that the response surface will have a regularity which matches the regularity of the input numbers. Based on the result of the analysis, we proposed an approach which is mainly concerned with a block of regular samples of prime size. One of the advantages is that, it eliminates the problem of the determination of the sample size beforehand. To support the proposed approach, we evaluate performance measures of a problem whose response through simulation is a wave.

Keywords


Simulation; Descriptive sampling; Bias evaluation; Response surface; Model.

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