From the 1 of 6 linked papers with an AI index.
6 papers
Models for species evolution with random deaths
Peter Braunsteins, Joseph Rolfe
The paper analyzes three discrete-time stochastic models of species evolution where births and deaths occur with given probabilities, focusing on how different rules for selecting…
Estimating Graph Dynamics from Population Observations
Peter Braunsteins, Michel Mandjes, Florian Montalescot
In this paper we consider a population process evolving on a dynamic random graph. The dynamic random graph is an ErdÅs--Rényi graph that is resampled every time unit, independen…
Infection models on dense dynamic random graphs
Simone Baldassarri, Peter Braunsteins, Frank den Hollander +1
We consider Susceptible-Infected-Recovered (SIR) models on dense dynamic random graphs, in which the joint dynamics of vertices and edges are co-evolutionary, i.e., they influence…
Intrinsic Whittle--Matérn fields and sparse spatial extremes
David Bolin, Peter Braunsteins, Sebastian Engelke +1
Intrinsic Gaussian fields are used in many areas of statistics as models for spatial or spatio-temporal dependence, or as priors for latent variables. However, there are two major…
Existence and non-existence of consistent estimators in supercritical controlled branching processes
Peter Braunsteins, Sophie Hautphenne, James Kerlidis
We consider the problem of estimating the parameters of a supercritical controlled branching process consistently from a single observed trajectory of population size counts. Our g…
Consistent least squares estimation in population-size-dependent branching processes
Peter Braunsteins, Sophie Hautphenne, Carmen Minuesa
We derive the first conditionally consistent estimators for a class of parametric Markov population models with logistic growth, which are suitable for modelling endangered populat…