Comparing two sequential Monte Carlo samplers for exact and approximate Bayesian inference on biological models
Bayesian methods are advantageous for biological modeling studies due to their ability to quantify and characterize posterior variability in model parameters. When Bayesian methods cannot be applied, due either to nondeterminism in the model or limitations on system observability, approximate Bayesi...
Autors principals: | Daly, A, Cooper, J, Gavaghan, D, Holmes, C |
---|---|
Format: | Journal article |
Publicat: |
Royal Society
2017
|
Ítems similars
-
Sequential Monte Carlo samplers
per: Del Moral, P, et al.
Publicat: (2006) -
Interacting sequential Monte Carlo samplers for trans-dimensional simulation
per: Jasra, A, et al.
Publicat: (2008) -
Monte Carlo samplers for efficient network inference.
per: Zeliha Kilic, et al.
Publicat: (2023-07-01) -
Approximating multivariate posterior distribution functions from Monte Carlo samples for sequential Bayesian inference.
per: Bram Thijssen, et al.
Publicat: (2020-01-01) -
Evolutionary Sequential Monte Carlo Samplers for Change-Point Models
per: Arnaud Dufays
Publicat: (2016-03-01)