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In this paper we shall consider optimal scaling problems for high-dimensional Metropolisâ€“Hastings algorithms where updates can be chosen to be lower dimensional than the target density itself. Weâ€¦ (More)

- Peter Neal, Gareth O. Roberts
- Biostatistics
- 2004

A stochastic epidemic model is proposed which incorporates heterogeneity in the spread of a disease through a population. In particular, three factors are considered: the spatial location of anâ€¦ (More)

- Peter Neal, Gareth Roberts
- Statistics and Computing
- 2005

In this paper, we introduce non-centered and partially non-centered MCMC algorithms for stochastic epidemic models. Centered algorithms previously considered in the literature perform adequately wellâ€¦ (More)

- Anne N. De Roeck, Udo Kruschwitz, +4 authors Nick Webb
- 1998

There are two reasons for doing this: (i) directories like Yellow Pages contain much useful but hard-to-access information, especially in the free text in semi-display advertisements; (ii) moreâ€¦ (More)

We consider the problem of optimal scaling of the proposal variance for multidimensional Random walk Metropolis (RWM) algorithms. It is well known, for a wide range of continuous target densities,â€¦ (More)

Integer valued AR (INAR) processes are perfectly suited for modelling count data. We consider the inclusion of explanatory variables into the INAR model to extend the applicability of INAR models andâ€¦ (More)

- Frank Ball, Tom Britton, Peter Neal
- J. Applied Probability
- 2016

We study continuous-time birth-death type processes, where individuals have independent and identically distributed lifetimes, according to a random variable Q, with E[Q] = 1, and where the birthâ€¦ (More)

- Victor Enciso-Mora, Peter Neal, MIMS EPrint
- 2006

We consider the problem of model (order) selection for integer valued autoregressive movingaverage (INARMA) processes. A very efficient Reversible Jump Markov chain Monte Carlo (RJMCMC) algorithm isâ€¦ (More)

- Fei Xiang, Peter Neal
- Computational Statistics & Data Analysis
- 2014

An efficient, generic and simple to use Markov chain Monte Carlo (MCMC) algorithm for partially observed temporal epidemic models is introduced. The algorithm is designed to be adaptive so that itâ€¦ (More)

Infectious diseases both within human and animal populations often pose serious health and socioeconomic risks. From a statistical perspective, their prediction is complicated by the fact that no twoâ€¦ (More)