Nonparametric Bayesian inference for discretely sampled diffusions We consider the nonlinear statistical inverse problem ofmaking inference on the unknown parameters of a diffusion processdescribing the solution of a stochastic differential…

Bayesian Factor Models in High Dimensions Sparse Bayesian factor models are routinely implemented for parsimonious dependence modeling and dimensionality reduction in high-dimensional applications. We provide theoretical understanding of such Bayesian…

Predicting the Present with Bayesian Structural Time Series This article describes a system for short term forecasting based on an ensemble prediction that averages over different combinations of predictors. The…

A Bayesian Nonparametric model for microbiome data analysis We develop a statistical model to analyse microbiome profiling data based on sequencing of genetic fingerprints in 16S ribosomal RNA. The analysis…

Bayesian modelling of networks in business intelligence problems Complex network data problems are increasingly common in many fields of application. Our motivation is drawn from strategic marketing studies monitoring customer…

Bayesian nonparametric approaches for the analysis of compositional data based on Bernstein polynomials We will discuss Bayesian nonparametric procedures for density estimation and fully nonparametric regression for compositional data, that…

Fast Quantification of Uncertainty and Robustness with Variational Bayes In Bayesian analysis, the posterior follows from the data and a choice of a prior and a likelihood. These choices may…

Path and parameter inference for Markov jump processes A variety of phenomena are best described using dynamical models which operate on a discrete state-space and in continuous time. The most…

Concentration inequalities in the infinite urn scheme for occupancy counts and the missing mass, with applications to Good-Turing estimators and adaptive statistical text compression An infinite urn scheme is defined…

Dependent Generalised Dirichlet Process Priors We propose a novel Bayesian nonparametric process prior for modelling a collections of random discrete distributions. This process is defined by combining a Generalised Dirichlet…

Functions, Manifolds and Statistical Linguistics Functional Data Analysis concerns the statistical study of curves and surfaces. An extension, Functional Object Data Analysis, looks at the statistical analysis of curves and…

High dimensional jump processes with stochastic volatility We deal with the problem of identifying jumps in multiple financial time series using the stochastic volatility model combined with a jump process.…

Branching Brownian motion with absorption What does the genealogy of a population under selection look like? This question is crucial for ecology and evolutionary biology and yet it is not…

Exact Bayesian inference for discretely observed jump-diffusions The standard approach to inference for parametric diffusion processesrelies on discretisation techniques (such as the Euler method) thatintroduce an approximation error difficult to…

Wasserstein distances and other metrics for discretely observed Lévy processes We present some upper bounds for the Wasserstein distance of order p between the product measures associated with the increments…

Stochastic Differential Equations as Jets We explain how Ito Stochastic Differential Equations (SDEs) on manifolds may be defined using 2-jets of smooth functions. We show how this relationship can be…

Saddlepoint techniques for dependent data Saddlepoint techniques provide numerically accurate, higher-order, small sample approximations to the distribution of estimators and test statistics. While a rich theory is available for saddlepoint…

Compound Random Measures Compound Random Measures (CoRM's) have been recently introduced by Griffin and Leisen (2017) and represent a general and tractable class of vectors of Completely Random Measures.  This…

Modelling Preference Data with the Wallenius Distribution The Wallenius distribution is a generalisation of the Hypergeometric distribution where weights are assigned to balls of different colours. This naturally defines a…