Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Straulino, Daniel"'
Publikováno v:
In Structural Change and Economic Dynamics December 2024 71:135-144
Knowledge of the spatial organisation of economic activity within a city is key to policy concerns. However, in developing cities with high levels of informality, this information is often unavailable. Recent progress in machine learning together wit
Externí odkaz:
http://arxiv.org/abs/2104.04545
Here we propose a new method to compare the modular structure of a pair of node-aligned networks. The majority of current methods, such as normalized mutual information, compare two node partitions derived from a community detection algorithm yet ign
Externí odkaz:
http://arxiv.org/abs/2010.06568
Autor:
Straulino, Daniel
This thesis focus on the effect that selection has on the ancestry of a spatially structured population. In the absence of selection, the ancestry of a sample from the population behaves as a system of random walks that coalesce upon meeting. Backwar
Externí odkaz:
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.664828
We ask the question "when will natural selection on a gene in a spatially structured population cause a detectable trace in the patterns of genetic variation observed in the contemporary population?". We focus on the situation in which 'neighbourhood
Externí odkaz:
http://arxiv.org/abs/1512.03766
We obtain the Brownian net of Sun and Swart (2008) as the scaling limit of the paths traced out by a system of continuous (one-dimensional) space and time branching and coalescing random walks. This demonstrates a certain universality of the net, whi
Externí odkaz:
http://arxiv.org/abs/1506.01158
Publikováno v:
The Annals of Applied Probability, 2017 Oct 01. 27(5), 2605-2645.
Externí odkaz:
https://www.jstor.org/stable/26361423
Akademický článek
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Akademický článek
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appendix with more detail on methods/results, robustness checks, and tables for reference;Figures in the main paper
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::30f9474b900f6d00b2b579043a45891d