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A definition of uncertainty based on posterior model probabilities of input variables to energy models is presented.
A discrimination criterion is developed based on posterior model probability that directly uses data to evaluate model importance.
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Sorensen & Waagepetersen [ 6] have applied a Markov chain Monte Carlo (MCMC) algorithm to estimate the parameters in a similar model, which has the advantage of producing model-checking tools based on posterior predictive distributions and model-selection criteria based on Bayes factor and deviances.
The ability of predicting growth was compared for the different models through predictive cross-validation using predictive log-scores of the models [ 17], approximated by evaluating the models based on posterior mean parameter estimates.
The predicted probabilities for screening from the latent class model, based on posterior medians, were dichotomized into screening and non-screening using a cut-off of 50% probability.
SSS is a variable selection model which allows the use of model averaging (based on posterior likelihood) for prediction.
Finally, like other genotype-calling algorithms based on posterior probabilities (e.g. MAQ), the model in SeqEM assumes that there are at most two distinct nucleotides within an individual at any position and in the sample as a whole.
Briefly, BMA methods estimate regression coefficients based on posterior probabilities of all (or m best) models considered.
Sire ranking based on posterior means of the sire effects from BS t and BN models for GL and BW compared using Kendall rank correlations are in Figure 5.
Class assignment was based on posterior probabilities.
Adding more background functions than are justified by the data (based on the posterior model ratio) may lead to a lower probability for the frequency and in some cases possibly a location shift.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com