74 citations · 122 across the 7 of their papers we have counts for
7 papers
Adaptive Sequential MCMC for Combined State and Parameter Estimation
Zhanglong Cao, David Bryant, Matthew Parry
In the case of a linear state space model, we implement an MCMC sampler with two phases. In the learning phase, a self-tuning sampler is used to learn the parameter mean and covari…
V-Splines and Bayes Estimate
Zhanglong Cao, David Bryant, Matthew Parry
Smoothing splines can be thought of as the posterior mean of a Gaussian process regression in a certain limit. By constructing a reproducing kernel Hilbert space with an appropriat…
Adaptive Smoothing for Trajectory Reconstruction
Zhanglong Cao, David Bryant, Tim Molteno +2
Trajectory reconstruction is the process of inferring the path of a moving object between successive observations. In this paper, we propose a smoothing spline -- which we name the…
Efficient recycled algorithms for quantitative trait models on phylogenies
Gordon Hiscott, Colin Fox, Matthew Parry +1
We present an efficient and flexible method for computing likelihoods of phenotypic traits on a phylogeny. The method does not resort to Monte-Carlo computation but instead blends…
Measuring the performance of sensors that report uncertainty
A. D. Martin, T. C. A. Molteno, M. Parry
We provide methods to validate and compare sensor outputs, or inference algorithms applied to sensor data, by adapting statistical scoring rules. The reported output should either…
Proper local scoring rules on discrete sample spaces
A. Philip Dawid, Steffen Lauritzen, Matthew Parry
A scoring rule is a loss function measuring the quality of a quoted probability distribution for a random variable , in the light of the realized outcome of ; it is p…