1 citations · 1 across the 3 of their papers we have counts for
7 papers
Parallel Tempering via Simulated Tempering Without Normalizing Constants
Biljana Jonoska Stojkova, David A. Campbell
In this paper we develop a new general Bayesian methodology that simultaneously estimates parameters of interest and the marginal likelihood of the model. The proposed methodology…
Incremental Mixture Importance Sampling with Shotgun optimization
Biljana Jonoska Stojkova, David A. Campbell
This paper proposes a general optimization strategy, which combines results from different optimization or parameter estimation methods to overcome shortcomings of a single method.…
Sequentially Constrained Monte Carlo
Shirin Golchi, David A. Campbell
Constraints can be interpreted in a broad sense as any kind of explicit restriction over the parameters. While some constraints are defined directly on the parameter space, when th…
Transdimensional Approximate Bayesian Computation for Inference on Invasive Species Models with Latent Variables of Unknown Dimension
Oksana A. Chkrebtii, Erin K. Cameron, David A. Campbell +1
Accurate information on patterns of introduction and spread of non-native species is essential for making predictions and management decisions. In many cases, estimating unknown ra…
Monotone Function Estimation for Computer Experiments
Shirin Golchi, Derek R. Bingham, Hugh Chipman +1
In statistical modeling of computer experiments sometimes prior information is available about the underlying function. For example, the physical system simulated by the computer c…
Bayesian Solution Uncertainty Quantification for Differential Equations
Oksana A. Chkrebtii, David A. Campbell, Ben Calderhead +1
We explore probability modelling of discretization uncertainty for system states defined implicitly by ordinary or partial differential equations. Accounting for this uncertainty c…