Sentence examples for evaluation of the marginal from inspiring English sources
The computationally expensive step in Bayesian model selection is the evaluation of the marginal likelihood, which is obtained by marginalizing over model parameters; i.e. P D0| m)=∫ f(D0| m, θ) P(θ| m) dθ, where P(θ| m) is the parameter prior for model m.
The optimization approach also provides clear convergence criteria for posterior approximation and facilitates model selection through automatic evaluation of the marginal likelihood.
Considering the suggestion of several authors, the evaluation of the marginal bone resorption after a period of more than a year after loading could be used as one of the indicators to predict the long-term prognosis of the implant because most implant failures occur within 1 year after loading.
As residual variance was not normally distributed but homoskedastic, Duan's non-parametric retransformation [36] factor (1.24 for Level 3 hospitals, 1.25 for Level 2 hospitals) was used in the evaluation of the marginal effects.
For (micro tensile strength values or evaluation of the marginal gap no such preference can be identified on the basis of the reviewed literature.
A more thorough evaluation of the marginal costs of the measures to be taken is also needed in order to balance lead exposure abatement options.
The initial step for the analysis requires the identification and evaluation of the appropriate marginal probability distribution.
The evaluation of anatomic form, marginal adaptation, proximal contact, the resistance to marginal discoloration, surface roughness, the absence of secondary caries, and post-operative pain yielded very satisfactory scores throughout the study.
Likelihood based inference for correlated data involves the evaluation of a marginal likelihood integrating out random effects.
The evaluation of the standard model and the marginal risk calculation in the source population (test performance) showed similar results compared to the evaluation in the study sample (apparent performance) (Table 4).
Target parameters of interest for evaluation of the imputation approaches were the marginal mean of the GHQ at wave 8 and the log odds of living at home at wave 9 given GHQ score at wave 8.
