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Optimal detection of changepoints with a linear computational cost
This work considers the problem of detecting multiple changepoints in large data sets and introduces a new method for finding the minimum of such cost functions and hence the optimal number and location of changepoints that has a computational cost which is linear in the number of observations.
A coalescent-based method for detecting and estimating recombination from gene sequences.
The extremely high level of recombination detected in both HIV1 and HIV2 sequences demonstrates that recombination cannot be ignored in the analysis of viral population genetic data and develops a powerful permutation-based method for detecting recombination that is both more powerful and robust to misspecification of the model of sequence evolution.
Constructing summary statistics for approximate Bayesian computation: semi‐automatic approximate Bayesian computation
This work shows how to construct appropriate summary statistics for ABC in a semi‐automatic manner, and shows that optimal summary statistics are the posterior means of the parameters.
Exact and efficient Bayesian inference for multiple changepoint problems
- P. Fearnhead
- Computer ScienceStat. Comput.
- 1 June 2006
The method can cope with a range of models, and exact simulation from the posterior distribution is possible in a matter of minutes, and can be useful within an MCMC algorithm, even when the independence assumptions do not hold.
On‐line inference for multiple changepoint problems
It is shown how resampling ideas from particle filters can be used to reduce the computational cost to linear in the number of observations, at the expense of introducing small errors, and two new, optimum resamplings algorithms are proposed for this problem.
Genome-wide association study of prostate cancer identifies a second risk locus at 8q24
Observations indicate the presence of at least two independent loci within 8q24 that contribute to prostate cancer in men of European ancestry, and it is estimated that the population attributable risk of the new locus, marked by rs6983267, is higher than the locus marked byrs1447295.
Improved particle filter for nonlinear problems
The Kalman filter provides an effective solution to the linear Gaussian filtering problem. However where there is nonlinearity, either in the model specification or the observation process, other…
Tracing the Source of Campylobacteriosis
The novel population genetics approach reveals that the vast majority (97%) of sporadic disease can be attributed to animals farmed for meat and poultry, whereas wild animal and environmental sources are responsible for just 3% of disease.
Exact and computationally efficient likelihood‐based estimation for discretely observed diffusion processes (with discussion)
Monte Carlo methods are proposed, which build on recent advances on the exact simulation of diffusions, for performing maximum likelihood and Bayesian estimation for discretely observed diffusions.
Estimating recombination rates from population genetic data.
A new method for estimating recombination rates from population genetic data using a computationally intensive statistical procedure (importance sampling) to calculate the likelihood under a coalescent-based model is introduced.