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...
Hoofdauteurs: | Daly, A, Cooper, J, Gavaghan, D, Holmes, C |
---|---|
Formaat: | Journal article |
Gepubliceerd in: |
Royal Society
2017
|
Gelijkaardige items
-
Sequential Monte Carlo samplers
door: Del Moral, P, et al.
Gepubliceerd in: (2006) -
Interacting sequential Monte Carlo samplers for trans-dimensional simulation
door: Jasra, A, et al.
Gepubliceerd in: (2008) -
Monte Carlo samplers for efficient network inference.
door: Zeliha Kilic, et al.
Gepubliceerd in: (2023-07-01) -
Approximating multivariate posterior distribution functions from Monte Carlo samples for sequential Bayesian inference.
door: Bram Thijssen, et al.
Gepubliceerd in: (2020-01-01) -
Evolutionary Sequential Monte Carlo Samplers for Change-Point Models
door: Arnaud Dufays
Gepubliceerd in: (2016-03-01)