71 citations · 78 across the 4 of their papers we have counts for
4 papers
A Note on Using Discretized Simulated Data to Estimate Implicit Likelihoods in Bayesian Analyses
M. S. Hamada, T. L. Graves, N. W. Hengartner +9
This article presents a Bayesian inferential method where the likelihood for a model is unknown but where data can easily be simulated from the model. We discretize simulated (cont…
Automatic Step Size Selection in Random Walk Metropolis Algorithms
Todd L. Graves
Practitioners of Markov chain Monte Carlo (MCMC) may hesitate to use random walk Metropolis-Hastings algorithms, especially variable-at-a-time algorithms with many parameters, beca…
A Maximum-Likelihood Analysis of Observational Data on Fluxes and Distances of Radio Pulsars: Evidence for Violation of the Inverse-Square Law
John Singleton, Pinaki Sengupta, John Middleditch +4
We analyze pulsar fluxes at 1400 MHz () and distances () extracted from the Parkes Multibeam Survey. Under the assumption that distribution of pulsar luminosities is d…
Advances in Data Combination, Analysis and Collection for System Reliability Assessment
Alyson G. Wilson, Todd L. Graves, Michael S. Hamada +1
The systems that statisticians are asked to assess, such as nuclear weapons, infrastructure networks, supercomputer codes and munitions, have become increasingly complex. It is oft…