Generalised Bayesian inference updates prior beliefs using a loss function, rather than a
likelihood, and can therefore be used to confer robustness against possible mis …

Since its inception the Metropolis-Hastings kernel has been applied in sophisticated ways to
address ever more challenging and diverse sampling problems. Its success stems from the …

Multiple-try Metropolis (MTM) is a popular Markov chain Monte Carlo method with the
appealing feature of being amenable to parallel computing. At each iteration, it samples …

This paper concerns differentially private Bayesian estimation of the parameters of a
population distribution, when a noisy statistic of a sample from that population is shared to …

In this paper, a novel online and adaptive truncation method is proposed for differentially
private Bayesian online estimation of a static parameter regarding a population. A local …

Details on priors: Full details of prior distributions used on the full set of parameters.
Likelihood computation: Details on how to compute the likelihood function using the JC69 …