This note presents the R package bayesGARCH (Ardia, 2007) which provides functions for the Bayesian estimation of the …

distribution. The second shows the relevance of the adaptive mixture procedure through the Bayesian estimation of a mixture of ARCH …

We develop a dynamic Bayesian model for clickthrough and conversion probabilities of paid search advertisements. These …

We investigate high-frequency volatility models for analyzing intra-day tick by tick stock price changes using Bayesian …

density of logreturns. Our proposed approach originates from the Bayesian approach to parameter estimation and time series …. This quasi-Bayesian approach yields more precise parameter estimation than a fully censored posterior for all parameters …, and has more focus on the region of interest than a standard Bayesian approach. The second main contribution is that we …

issues exist that involve multimodal data distributions. We propose a Bayesian approach using mixtures distributions to … shapes such as multimodality and long tails. Our simulation-based Bayesian inference treats the density features as random …