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At the offset of a (stochastic) epidemic, it is of importance to have a mathematical model that will assist in the making of an informed judgement on whether the epidemic will explode, or will be minor and die out. In this paper, we consider probabilistic inferences related to the event of extinction of a discrete time branching process when this cannot be(More)
Acknowledgments This present work, similar to a hike in the mountains of Switzerland, has taken time to achieve. This long-term project leaves some memories of people to whom I would like to express my gratitude. I would like to express my deepest gratitude to my supervisor, Professor Stephan Morgenthaler for his continuous encouragement, patience, guidance(More)
We propose a novel method for the analysis of spatially distributed data from an exponential family distribution, able to efficiently treat data occurring over irregularly shaped domains. We consider a generalized linear framework and extend the work of Sangalli et al. (2013) to distributions other than the Gaussian. In particular, we can handle all(More)