Sentence examples for using a prior derived from inspiring English sources

An increase in accuracy of 1-2% for all traits was observed in the Australian Holstein population when using a prior derived from the Nordic Holstein population compared to using no prior information.

Results showed an increase in accuracy of up to 3.5% for the Jersey population when using BayesRS with a prior derived from Australian Holstein compared to a model without location specific priors.

Subsequently, the composite likelihood ratios are converted into posterior odds and finally into posterior probabilities by using a prior odds estimate that is derived from the statistics estimated using the validation data (Incyte YPD interactions).

The DACS Network was constructed using a prior knowledge of causal relationships from literature, and augmented with nodes derived from RCR, a data-driven method that infers pathway activity based on differentially expressed entities and knowledge of their upstream regulators.

The second best method in terms of correlation with AGS (0.74) and MSE (0.09) was the Bayesian method that uses normal mixture prior derived from predictions of the 2001 mixed effects applied in the 2002 context.

The Bayesian framework underlying the approach potentially allows application to any amount of data by using informative priors derived from previous translocations or expert opinion.

Significant life events in the six months prior to the act of non-fatal self-poisoning was examined using a questionnaire derived from the Bughra Life Threatening Events Questionnaire [ 37].

In the work presented here, we perform 100 bootstrap operations for each of four cases: gene expression data alone (with no priors), or using priors derived from the literature, from PPI data, or from a combination of the two.

24 Using a proportionality formula derived from an intrauterine fetal weight standard, 25 optimal weights for births occurring prior to 280 days are calculated.

Bayesian Networks are graphical probabilistic models in which predictions are obtained using prior probabilities derived from either measured data or expert opinion.

We did this for several different models that use previously proposed interaction priors as well as the prior derived from causal inference.