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The standard GTAP modeling framework uses a one-to-one relationship between industries and commodities.
The modeling framework uses a multilayer infrastructure network (MIN) concept, the computable general equilibrium (CGE) theory, and its spatial extension (SCGE), to formulate an equilibrium problem.
This modeling framework uses a Markov chain Monte Carlo approach to generate samples from parameters' posterior distributions.
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The oil reservoir, being treated as a multi-input, multi-output (MIMO) system in terms of injection inputs and production outputs, is identified within a robust surrogate modeling framework using a frequency-based system identification approach.
We illustrate the proposed modeling framework using lignite data from the Mavropigi mine in Northern Greece.
The general modeling framework used in our study is as follows.
The Petri net modeling framework used in this work has been derived from the seminal work of Chaouiya et al. (2006).
However, unlike SQN and SWAN, BMIQ is based on an explicit beta-mixture modeling framework, and uses state-membership probabilities under this beta mixture model to reassign the quantiles of the type2 probes according to the type1 distribution.
A pathway modeling framework that uses deterministic or stochastic differential equation models requires a priori knowledge of the structure of the biochemical reaction network, mathematical functional forms for the biochemical reactions, and associated reaction rate constants.
A generalized linear modeling framework was used to investigate seroprevalence patterns in domestic dogs and wildlife with a binary outcome (seronegative or seropositive) and binomial error structure.
Further, the linear modeling framework often used for GWAS analysis usually considers only one SNP at a time thus ignoring the genomic and environmental context of each SNP (Moore and Williams, 2009).
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