Results 51 to 60 of about 103,187 (313)

Bayesian Model Selection of Regular Vine Copulas [PDF]

, 2018
Regular vine copulas are a flexible class of dependence models, but Bayesian methodology for model selection and inference is not yet fully developed.
Gruber, L. and Czado, D.
core   +1 more source

Implementing and testing Bayesian and maximum-likelihood supertree methods in phylogenetics [PDF]

Royal Society Open Science, 2015
Since their advent, supertrees have been increasingly used in large-scale evolutionary studies requiring a phylogenetic framework and substantial efforts have been devoted to developing a wide variety of supertree methods (SMs).
Wasiu A. Akanni, Mark Wilkinson, Christopher J. Creevey, Peter G. Foster, Davide Pisani   +4 more
doaj   +1 more source

Bayesian Network Inference Using Marginal Trees [PDF]

International Journal of Approximate Reasoning, 2014
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Cory J. Butz, Jhonatan de S. Oliveira, Anders L. Madsen   +2 more
openaire   +2 more sources

Tractable Bayesian learning of tree belief networks [PDF]

Statistics and Computing, 2006
Appears in Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence (UAI2000)
Marina Meila, Tommi S. Jaakkola
openaire   +3 more sources

Hierarchical change-point regression models including random effects to estimate empirical critical loads for nitrogen using Bayesian Regression Models (brms) and JAGS

MethodsX, 2022
The concept of critical loads is used in the framework of the Convention on Long-range Transboundary Air Pollution (UNECE) to define thresholds below which no damaging effects on habitats occur based on the latest scientific knowledge.
Tobias Roth, Simon Tresch, Enzai Du, Sabine Braun   +3 more
doaj   +1 more source

Tree models: a Bayesian perspective [PDF]

, 2006
Submitted in partial fulfilment of the requirements for the degree of Master of Philosophy at Queen Mary, University of London, November 2006Classical tree models represent an attempt to create nonparametric models which have good predictive powers as ...
Egan, Blaise
core  

A Bayesian nonparametric approach to testing for dependence between random variables [PDF]

, 2016
Nonparametric and nonlinear measures of statistical dependence between pairs of random variables are important tools in modern data analysis. In particular the emergence of large data sets can now support the relaxation of linearity assumptions implicit ...
Filippi, Sarah, Filippi, S, Holmes, Chris, Holmes, C   +3 more
core   +1 more source

Bayesian tree. [PDF]

, 2021
Maximum clade credibility tree was conducted based on Bayesian Method. The tree branch length is presented in MYA while the color of the branch represents the posterior probability. A total of 2097 sequences from the global library and our collected head
Atchara Phumee (530776), Kobpat Phadungsaksawasdi (9853194), Sakone Sunantaraporn (9853191), Vorthon Sawaswong (3482735), Switt Kongdachalert (9853200), Nirin Seatamanoch (9853197), Narisa Brownell (9853188), Sunchai Payungporn (112134), Kanyarat Kraivichian (673114), Padet Siriyasatien (669580)   +9 more
core   +1 more source

Reconstructing enzyme evolution by protein engineering

FEBS Letters, EarlyView.
Natural enzyme evolution can be retraced by protein engineering methods such as directed evolution, rational design, and ancestral sequence reconstruction. These approaches reveal how enzymes emerged from ligand‐binding scaffolds, developed varying substrate preferences, formed oligomeric complexes, adapted to environmental changes, and evolved novel ...
Lukas Drexler, Markus R. Busch, Reinhard Sterner   +2 more
wiley   +1 more source

Predicting Facial Biotypes Using Continuous Bayesian Network Classifiers

Complexity, 2018
Bayesian networks are useful machine learning techniques that are able to combine quantitative modeling, through probability theory, with qualitative modeling, through graph theory for visualization.
Gonzalo A. Ruz, Pamela Araya-Díaz
doaj   +1 more source