Seminars in Statistics
Seminars in Statistics
Seminars in Statistics Laura Ventura (University of Padua)
Robust Approximate Bayesian Inference The likelihood function is the basis of both frequentist and Bayesian methods. However, the stability of likelihood-based procedures requires strict adherence to the model assumptions: mild…
Seminars in Statistics Richard Nickl (University of Cambridge)
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…
Seminars in Statistics Natesh Pillai (Harvard University)
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…
Seminars in Statistics Steven Scott (Google)
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…
Seminars in Statistics Boyu Ren (Harvard T.H. Chan School of Public Health)
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…
Seminars in Statistics Bruno Scarpa (University of Padua)
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…
Seminars in Statistics Alejandro Jara (Pontificia Universidad Católica de Chile)
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…
Seminars in Statistics Tamara Broderick (MIT)
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…
Seminars in Statistics Vinayak Rao (Purdue University)
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…
Seminars in Statistics Stéphane Boucheron (Université Paris-Diderot)
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…
Seminars in Statistics Maria De Iorio (University College London)
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…
Seminars in Statistics John Aston (University of Cambridge)
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…
Seminars in Statistics Petros Dellaportas (University College London)
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.…
Seminars in Statistics Julien Berestycki (University of Oxford)
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…
Seminars in Statistics Kazuhiko Kakamu (Kobe University)
How does monetary policy affect income inequality in Japan? Evidence from grouped data Co-author: Martin Feldkircher (Oesterreichische Nationalbank (OeNB)) Abstract: We examine the effects of monetary policy on income inequality…
Seminars in Statistics Krzysztof Łatuszyński (University of Warwick)
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…
Seminars in Statistics Ester Mariucci (Humboldt-Universität zu Berlin)
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…
Seminars in Statistics John Armstrong (King’s College London)
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…
Seminars in Statistics Davide La Vecchia (University of Geneva)
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…
Seminars in Statistics Fabrizio Leisen (University of Kent)
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…