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The coordinate distances between points on the B0 and B∞ axes can be written respectively as βL = ln ρ1η1)/(ρ2η2) and βL = ln ρ1/ρ2), which notably are the bias factors for models described in ref (8) and occur as special consequences of the formalism presented here (seventh section of Theoretical Calculations).
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It is interesting to note that the odds ratios were very similar in models with fewer factors (for example, Model 3) and in models with more factors included (for example, Models 9 and 11).
We gain insight from the marginal likelihoods, by computing Bayes factors, for model comparison and model selection.
Currently used probabilistic models and derived factors for model uncertainties are mostly based on intuitive judgements and limited data.
The transmissivity and storativity are very important factors for modeling groundwater productivity because they control the ability of a specific water bearing layer to transmit and store water.
All the variables of interest, including the Bayes factors for model selection, the posterior distributions of model parameters, and the averaged results of system responses are obtained by one reversible jump Markov chain Monte Carlo simulation.
The 5% significance level was used when assessing factors for model inclusion.
The analytical expressions make it possible to compare the JSD to distributions of the actual Bayes factors for model selection.
The model predictions are reliable over several timescales and in the presence of strong temperature fluctuations, which are crucial factors for modeling marine organism growth.
Bayes Factors for model comparisons (and their uncertainties) have been calculated for each of the three independent runs via thermodynamic integration [ 37].
Comparative studies of the genetic structure of populations, particularly those utilising molecular makers, have provided new opportunities for better understanding historical and/or contemporary factors for modelling speciation.
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