Abstract
This paper presents a new linear regression- based approach for developing mathematical models suitable for use in management and operations training simulators. This novel approach modifies static cost-independent regression models into dynamic accountable simulator models that translate input resource decisions into output performance feedback. Entirely new techniques have been developed for accounting for time, determining resource allocation cost rates, translating resource allo cation into technical performance, and incor porating probabilistic effects. These techniques offer both empirical and probabilistic advan tages over existing methods.
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