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In addition, the distribution of model parameters possessed long tails, favouring the (L_1) norm approach.
A stationary distribution of model (1.2) with the ergodic property is investigated.
Figure 2 Frequency distribution of model distribution ratios (MDR) for "most similar endpoints".
Figure 4 Frequency distribution of model distribution ratios (MDR) for fungicidal combination products.
Figure 3 Frequency distribution of model distribution ratios (MDR) for herbicidal combination products.
A skewness parameter of 0.3 ensures a nearly normal distribution of model misfit to field observations.
The goal of Bayesian inference is to estimate the posterior distribution of model parameters Φ.
The stress distribution of model components, including steel beams, steel tubes, and concrete cores are illustrated.
Figure 4 shows the Incidence Rate Ratios (IRR) for each factor, as well as the distribution of model dispersion.
Bayesian inference is based on the posterior distribution of model parameters, which is not of a known form.
The particle size distribution of model soil was approximated by the combination of cylinders of two radii.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com