Sentence examples for a posterior distribution of from inspiring English sources
This approach considers prior information about the distribution of parameters along with the likelihood of the observed data to construct a posterior distribution of relevant quantities for inference about unknown parameters.
PVs are draws from a posterior distribution of θ i for individual i, given that individual's responses to items on a test and a set of background characteristics in a "conditioning model".
Bayes' theorem is used to link the prior distribution to the actual data distribution (analogously, the likelihood) yielding a posterior distribution of the model parameters (see Kaplan and Depaoli 2013, for an overview of Bayesian inference).
SBL is comparable to HB-Kalman, as it is a CS method and satisfies the requirement of our method that it can estimate a posterior distribution of the unknown image.
To compensate for this lack of information, each masked estimated source is considered as uncertain and described in the form of a posterior distribution of each Fourier coefficient of the clean signal given the available information.
Here we apply an approximate Bayesian computation (ABC) parameter inference method, which produces a posterior distribution of D and λ, to new sets of synthetic data, generated from an idealised mathematical model, and experimental data for a non-adhesive mesenchymal population of fibroblast cells.
(A ) Posterior distributions of the selection coefficient and hybrid population size from ABC simulations for Tlatemaco and (B ) Calnali.
Each conditional distribution is a conditional posterior distribution of a parameter value given the last sampled values of the other parameters and the data.
In addition, plots show a wider posterior distribution of the OR for the exposure to PFHxS, suggesting a bigger uncertainty in the risk associated to this exposure.
The variants, which were not confirmed, exhibited a bimodal posterior distribution of frequency differences.
For stature, udder score and feet and legs score, the estimated dominance variance was clearly larger with both Gibbs sampling analyses than with REML estimation because of a skewed posterior distribution of the Gibbs samples.
