Sentence examples for model and posterior from inspiring English sources

The following three t-statistics were computed for each gene in g: (2) (3) (4) Finally, the DE measurement contrasts in (2, 3, 4) were processed by fitting a two-component normal mixture model and posterior probabilities of belonging to the non-null component were used to identify DE genes with an estimated experiment-wise false discovery rate of < 1% as described by McLachlan et al. [ 21].

Algorithms for computing output sensitivities to parameter variances, model evidence and posterior model plausibilities for given data, and for computing what are referred to as Occam Categories in reference to a rough measure of model simplicity, make up components of the overall approach.

He is particularly interested in developing Bayesian models and posterior inference techniques that address the Big Data problem, with applications to data analysis and exploration, recommendation systems, information retrieval, and compressed sensing.

In summary, the approaches we described use a developed unified dynamic test framework that includes SETI with statistical significance testing, ranking temporal genes by AR(1) modeling and posterior probability of autocorrelation parameter, and HMM to classify temporal dynamic patterns.

Evolutionary models and posterior predictive approaches favoured an early shift to a new adaptive peak over decreasing rates of evolution as the underlying process driving the early divergence of locomotor phenotypes.

The visual predictive checks (VPCs) of the two-level models and posterior predictive check (analogous to a VPC, see Supplementary Information 3) of the three-level Bayesian model used to investigate whether modeling between-study variability improves the predictive properties of the model are presented in Supplementary Figure S3.

In a welfare-based setting, we estimate by Bayesian methods a number of variants of a New Keynesian macroeconomic model and use both the model odds and posterior densities to design robust interest rate rules consisting of an inflation-forecast-based rule and a wage-targeting one.

Fig. 2 Posterior Model Size Distribution and Posterior Model Probabilities: model size reflects the number of variables suggested by prior and posterior distribution of potential variables (mean 7.003).

Model ranking by the marginal likelihood provides information regarding the model uncertainty, and posterior inclusion probabilities of covariates offer an intuitive and convenient aid to subset selection.

Details about Bayesian computation, including the full probability model and full posterior conditionals, can be found in the Supplementary Material.

First, he presents a systematic Bayesian probabilistic estimation framework in which we can define and compute the prior model, the sensor model, and the posterior model.