290 citations · 303 across the 7 of their papers we have counts for
7 papers
Nonparametric Bayesian inference for the Gini-Simpson index
Pier Giovanni Bissiri, Riccardo Corradin, Andrea Ongaro
Many statistical problems concern the analysis of species distributions or, more generally, of discrete labeled quantities. Assessing species diversity constitutes a key step towar…
Posterior inference via Hill's prediction model
Pier Giovanni Bissiri, Chris Holmes, Stephen G. Walker
This paper is concerned with the construction of prior free posterior distributions which rely on the use of one step ahead predictive distribution functions. These are typically m…
A new look at fiducial inference
Pier Giovanni Bissiri, Chris Holmes, Stephen Walker
Since the idea of fiducial inference was put forward by Fisher, researchers have been attempting to place it within a rigorous and well motivated framework. It is fair to say that…
Relations between Schoenberg Coefficients on Real and Complex Spheres of Different Dimensions
Pier Giovanni Bissiri, Valdir A. Menegatto, Emilio Porcu
Positive definite functions on spheres have received an increasing interest in many branches of mathematics and statistics. In particular, the Schoenberg sequences in the spectral…
A General Framework for Updating Belief Distributions
Pier Giovanni Bissiri, Chris Holmes, Stephen Walker
We propose a framework for general Bayesian inference. We argue that a valid update of a prior belief distribution to a posterior can be made for parameters which are connected to…
A definition of conditional probability distribution with non-stochastic information
Pier Giovanni Bissiri, Stephen G. Walker
The current definition of a conditional probability distribution enables one to update probabilities only on the basis of stochastic information. This paper provides a definition f…
On Bayesian learning from Bernoulli observations
Pier Giovanni Bissiri, Stephen G. Walker
We provide a reason for Bayesian updating, in the Bernoulli case, even when it is assumed that observations are independent and identically distributed with a fixed but unknown par…