A Theoretical Study of Process Dependence for Standard Two-Process Serial Models and Standard Two-Process Parallel Models
Ru Zhang, Yanjun Liu, James T. Townsend

TL;DR
This theoretical study differentiates serial and parallel two-process models by analyzing their dependence structures and distributional behaviors, revealing key distinctions in process dependence and implications for empirical observations.
Contribution
It provides a mathematical characterization of process dependence in standard two-process serial and parallel models without assuming specific distribution forms.
Findings
Serial models do not exhibit positive dependence without specific distributions.
Parallel models have independent total completion times.
Survival functions depend on hazard function properties.
Abstract
In this article we differentiate and characterize the standard two-process serial models and the standard two process parallel models by investigating the behavior of (conditional) distributions of the total completion times and survivals of intercompletion times without assuming any particular forms for the distributions of processing times. We address our argument through mathematical proofs and computational methods. It is found that for the standard two-process serial models, positive dependence between the total completion times does not hold if no specific distributional forms are imposed to the processing times. By contrast, for the standard two-process parallel models the total completion times are independent. According to different nature of process dependence, one can distinguish a standard two process serial model from a standard two-process parallel model. We also find that…
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Taxonomy
TopicsReliability and Maintenance Optimization · Statistical Distribution Estimation and Applications
