Abbreviations: APC: apical pore complex; BI: Bayesian inference
; BS: Bootstrap support; BSA: Bovine serum albumin; BSE: Back scatter electron; CFP: Ciguatera fish poisoning; CTXs: Ciguatoxins; DNA: Deoxyribonucleic acid; LC-MS/MS: Liquid chromatography-mass spectrometry/mass spectrometry; LSU rDNA: Large subunit ribosomal DNA; ML: Maximum likelihood; MTXs: Maitotoxins; PCR: Polymerase chain reaction; Po: outer pore plate; PP: Posterior probability; SE: Secondary electron; SEM: Scanning electron microscopy; SSU rDNA: Small subunit ribosomal DNA
was employed to obtain the joint posterior distribution for the unknown parameters of each growth model separately for male and female sheep and singles and twin sheep.
The components of (co) variance and genetic parameters were estimated via linear and threshold animal model by Bayesian inference
in single and two-trait analyses.
The Bayesian inference
and MaxEnt are such approaches.
Furthermore, isotopic niche studies should be compared to each other in terms of SEAc and the uncertainty surrounding such values, based on Bayesian inference
and probability distributions.
As suggested before, the progressive introduction of Bayesian inference
in the mainstream of resea rch practise is not easy and some disagreements should be fixed in the go (see, for example, Hoijtink et al., 2016).
In order to build a causal network among factors in NAS, it is important to incorporate Bayesian inference
in data-mining process.
Yang, "Fuzzy Bayesian inference
," in Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, Computational Cybernetics and Simulation, pp.
It is well known that Bayesian inference
operates on the basis of the posterior distribution p(H, [alpha], [eta] | X) = p(H, [alpha], [eta], X)/p(X.
Cafaro, "Information geometry and chaos on negatively curved statistical manifolds," in Proceedings of the 27th International Workshop on Bayesian Inference
and Maximum Entropy Methods in Science and Engineering, MaxEnt 2007, pp.
Wang incorporate background knowledge into Bayesian inference
to isolate the problem source degrading the control loop performance.
For Bayesian inference
about treatment effect, a test is required to determine whether the posterior probability of treatment proportions [P.sub.t] and [P.sub.c] lies within the bounds of the equivalence margin or not.