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Wireload models are statistical models that are used by Design Compiler to estimate wiring loading between cells in a design.
DFN models are statistical models which define the density of fractures having given geometrical properties (size and orientation) and which include an intrinsic variability term.
These regression models are statistical rather than mechanistic.
Prognostic models are statistical models that combine two or more items of patient data to predict clinical outcome.
Predictors were centered to have mean 0 and scaled to have standard deviation 1. Mixed models are statistical models that incorporate both fixed-effects parameters and random effects.
2 Intensive care mortality prediction models are statistical methods designed to predict hospital mortality on the basis of patient data collected during admission to an intensive care unit (ICU).
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The approach employed, in deriving the mathematical models, is statistical (black-box method), a process that is referred to as system identification [33].
One of the earliest models is statistical positioning, which involves DNA sequence features acting as boundary constraints to the distribution of nucleosomes.
The mathematical methods based on the statistical method of statistical model are statistical modeling and Bayes theory [1].
Software reliability growth models (SRGM) are statistical interpolation of software failure data by mathematical functions.
Linear models are a statistical approach similar to ANOVA, which generalize both ANOVAs and linear regressions.
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