Modelling with discrete random probability measures

Random probability measures are a cornerstone of Bayesian nonparametrics. By virtue of de Finetti's representation theorem, their law acts as the prior distribution for exchangeable observations. Mostly used Bayesian nonparametric procedures, in this framework, rely on laws selecting almost surely discrete probability measures, such as the celebrated Dirichlet process and its several extensions. The first part of this thesis is dedicated to problems related to random probability measures arising in the exchangeable regime. We explore properties of functionals of noteworthy discrete random probability measures in order to provide prior elicitation. In particular we retrieve explicit expressions for base measures inducing a broad class of distributions on the random mean of a Dirichlet process, a normalized stable process and a Pitman--Yor process. We furthermore provide an application to widely employed mixture models. These results have led us to further theoretical investigations regarding the connection between Dirichlet random means and continual Young diagrams. The second part of the thesis is instead devoted to the partially exchangeable regime, a generalization of exchangeability which encompasses a more complex dependence structure among observations naturally divided in groups. We rely on hierarchical discrete random probability measures to enforce such distributional invariance in a model for clustering of nodes in multilayer networks. The induced distribution on the space of sequences of consistent partitions, determined by partially exchangeable partition probability functions, allows for theoretically validated prediction regarding new nodes incoming into the network

Specification of the base measure of nonparametric priors via random means

Functionals of random probability measures are probabilistic objects whose properties are studied in different fields. They also play an important role in Bayesian Nonparametrics: understanding the behavior of a finite dimensional feature of a flexible and infinite-dimensional prior is crucial for prior elicitation. In particular distributions of means of nonparametric priors have been the object of thorough investigation in the literature. We target the inverse path: the determination of the parameter measure of a random probability measure giving rise to a fixed mean distribution. This direction yields a better understanding of the sets of mean distributions of notable nonparametric priors, giving moreover a way to directly enforce prior information, without losing inferential power. Here we summarize and report results obtained in [6] for the Dirichlet process, the normalized stable random measure and the Pitman–Yor process, with an application to mixture models

Integrated strategies for allogeneic blood saving in major elective surgery

Background: Large use of allogeneic red blood cell concentrates (RBCc), albeit necessary in major surgery, may influence patients' outcome. Design and methods: We introduced an integrated strategy including patients' evaluation and supplementation associated with autologous blood collection and saving to support major elective surgery at our hospital since 2008. After 2 years of stabilization of this approach, we analyzed the results obtained in 2010 in terms of allogeneic blood usage and reduction of transfusion of stored RBCc. Results: Analyzing 2010 results we found that usage of total autologous RBCc units was increased by 2.2 folds, of "not stored" autologous RBCc units by 2.4 folds and of allogeneic RBCc unit transfusion reduced by 65%. The significant reduction in the number of transfused allogeneic RBCc units associated with the use of "fresher" blood could prevent patients' complications due to immunomodulation and biologic/metabolic disregulation. (C) 2011 Elsevier Ltd. All rights reserved

Evaluation of Human Disturbance on the Activity of Medium–Large Mammals in Myanmar Tropical Forests

The effects of human disturbance represent one of the major threats for wildlife conservation. Many studies have shown that wildlife avoids or reduces direct contact with human activities through changes in activity patterns, and by minimizing spatiotemporal overlap. In this study, we investigated the possible effects of human presence on the temporal activity of medium-to-large mammals using two areas in Myanmar that differ in the intensity of human disturbance. We monitored temporal segregation mechanisms using camera trapping data and with two statistical approaches: daily activity overlaps between humans and wildlife and circular statistics. We did not find a significant difference in overlapping activity between areas but, thanks to circular statistics, we found that some species show changes in activity patterns, suggesting temporal avoidance. We observed that the daily activity of five species differed between areas of Myanmar, likely adopting mechanisms to reduce overlap in areas highly frequented by humans. Interestingly, these species are all threatened by hunting or poaching activities, four of which have been described in literature as “cathemeral”, or species that are active through day and night. This study suggests that some species adapt their behavior, at least partially, to avoid human presence in habitats with higher anthropic occurrence and increase our knowledge on the status of medium–large mammals in a poorly studied country as Myanmar

Evaluation of Human Disturbance on the Activity of Medium–Large Mammals in Myanmar Tropical Forests

The effects of human disturbance represent one of the major threats for wildlife conservation. Many studies have shown that wildlife avoids or reduces direct contact with human activities through changes in activity patterns, and by minimizing spatiotemporal overlap. In this study, we investigated the possible effects of human presence on the temporal activity of medium-to-large mammals using two areas in Myanmar that differ in the intensity of human disturbance. We monitored temporal segregation mechanisms using camera trapping data and with two statistical approaches: daily activity overlaps between humans and wildlife and circular statistics. We did not find a significant difference in overlapping activity between areas but, thanks to circular statistics, we found that some species show changes in activity patterns, suggesting temporal avoidance. We observed that the daily activity of five species differed between areas of Myanmar, likely adopting mechanisms to reduce overlap in areas highly frequented by humans. Interestingly, these species are all threatened by hunting or poaching activities, four of which have been described in literature as “cathemeral”, or species that are active through day and night. This study suggests that some species adapt their behavior, at least partially, to avoid human presence in habitats with higher anthropic occurrence and increase our knowledge on the status of medium–large mammals in a poorly studied country as Myanmar