Time series of financial asset values exhibit well-known statistical features such as heavy tails and volatility clustering. We propose a nonparametric extension of the classical Peaks-Over-Threshold method from extreme value theory to fit the time varying volatility in situations where the...

A Bayesian solution is suggested for the modelling of spatial point patterns with inhomogeneous hard-core radius using Gaussian processes in the regularization. The key observation is that a straightforward use of the finite Gibbs hard-core process likelihood together with a log-Gaussian random...

We develop a Bayesian dynamic model for modeling and forecasting multivariate time series relaxing the assumption of normality for the initial distribution of the state space parameter, and replacing it by a more flexible class of distributions, which we call Generalized Skew-Normal (GSN)...

Because technology-enabled marketing research has led to information arriving at a rapid pace, methods in marketing that allow for coherent, sequential and fast information integration are needed. We propose in this research a new approach to information integration: Information Reweighted...

The relative importance of permanent versus cyclical shocks to GDP has been found to depend on the presence or absence of a single break in mean growth. We estimate unobserved components models conditional on a trend break having occurred in any specified quarter and use the Bayesian model...

Traffic flow data are primarily used to monitor road use and to compute road accident rates in Great Britain. The main traffic flow data used for these purposes measure annual traffic flow in vehicle kilometres, however this dataset is limited in its disaggregation. In particular, it is not...

Joint models for longitudinal and survival data are often used to investigate the association between longitudinal data and survival data in many studies. A common assumption for joint models is that random effects are distributed as a fully parametric distribution such as multivariate normal...

Using the concept of the stochastic discount factor with critical behavior, we present a self-consistent model for explosive financial bubbles, which combines a mean-reverting volatility process and a stochastic conditional return which reflects nonlinear positive feedbacks and continuous...

Diaconis and Ylvisaker (1979) give necessary conditions for conjugate priors for distributions from the natural exponential family to be proper as well as to have the property of linear posterior expectation of the mean parameter of the family. Their conditions for propriety and linear posterior...