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Search Results: 1 - 10 of 29 matches for " Hankin "
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A short note on Simulation and Abstraction
Chris Hankin
Computer Science , 2013, DOI: 10.4204/EPTCS.129.20
Abstract: This short note is written in celebration of David Schmidt's sixtieth birthday. He has now been active in the program analysis research community for over thirty years and we have enjoyed many interactions with him. His work on characterising simulations between Kripke structures using Galois connections was particularly influential in our own work on using probabilistic abstract interpretation to study Larsen and Skou's notion of probabilistic bisimulation. We briefly review this work and discuss some recent applications of these ideas in a variety of different application areas.
Introducing multivator : A Multivariate Emulator
Robin K. S. Hankin
Journal of Statistical Software , 2012,
Abstract: A multivariate generalization of the emulator technique described byHankin (2005) is presented in which random multivariate functions may be assessed. In the standard univariate case (Oakley 1999), a Gaussian process, a nite number of observations is made; here, observations of different types are considered. The technique has the property that marginal analysis (that is, considering only a single observation type) reduces exactly to the univariate theory. The associated software is used to analyze datasets from the field of climate change.
A Generalization of the Dirichlet Distribution
Robin K. S. Hankin
Journal of Statistical Software , 2010,
Abstract: This paper discusses a generalization of the Dirichlet distribution, the ‘hyperdirichlet’, in which various types of incomplete observations may be incorporated. It is conjugate to the multinomial distribution when some observations are censored or grouped. The hyperdirichlet R package is introduced and examples given. A number of statistical tests are performed on the example datasets, which are drawn from diverse disciplines including sports statistics, the sociology of climate change, and psephology.
Introducing untb, an R Package For Simulating Ecological Drift Under the Unified Neutral Theory of Biodiversity
Robin K. S. Hankin
Journal of Statistical Software , 2007,
Abstract: The distribution of abundance amongst species with similar ways of life is a classical problem in ecology. The unified neutral theory of biodiversity, due to Hubbell, states that observed population dynamics may be explained on the assumption of per capita equivalence amongst individuals. One can thus dispense with differences between species, and differences between abundant and rare species: all individuals behave alike in respect of their probabilities of reproducing and death. It is a striking fact that such a parsimonious theory results in a non-trivial dominancediversity curve (that is, the simultaneous existence of both abundant and rare species) and even more striking that the theory predicts abundance curves that match observations across a wide range of ecologies. This paper introduces the untb package of R routines, for numerical simulation of ecological drift under the unified neutral theory. A range of visualization, analytical, and simulation tools are provided in the package and these are presented with examples in the paper.
Introducing BACCO, an R Bundle for Bayesian Analysis of Computer Code Output
Robin K. S. Hankin
Journal of Statistical Software , 2005,
Abstract:
Introducing elliptic, an R Package for Elliptic and Modular Functions
Robin K.S. Hankin
Journal of Statistical Software , 2006,
Abstract: This paper introduces the elliptic package of R routines, for numerical calculation of elliptic and related functions. Elliptic functions furnish interesting and instructive examples of many ideas of complex analysis, and the package illustrates these numerically and visually. A statistical application in fluid mechanics is presented.
Multi-scale Community Detection using Stability Optimisation within Greedy Algorithms
Erwan Le Martelot,Chris Hankin
Computer Science , 2012,
Abstract: Many real systems can be represented as networks whose analysis can be very informative regarding the original system's organisation. In the past decade community detection received a lot of attention and is now an active field of research. Recently stability was introduced as a new measure for partition quality. This work investigates stability as an optimisation criterion that exploits a Markov process view of networks to enable multi-scale community detection. Several heuristics and variations of an algorithm optimising stability are presented as well as an application to overlapping communities. Experiments show that the method enables accurate multi-scale network analysis.
Fast Multi-Scale Community Detection based on Local Criteria within a Multi-Threaded Algorithm
Erwan Le Martelot,Chris Hankin
Computer Science , 2013,
Abstract: Many systems can be described using graphs, or networks. Detecting communities in these networks can provide information about the underlying structure and functioning of the original systems. Yet this detection is a complex task and a large amount of work was dedicated to it in the past decade. One important feature is that communities can be found at several scales, or levels of resolution, indicating several levels of organisations. Therefore solutions to the community structure may not be unique. Also networks tend to be large and hence require efficient processing. In this work, we present a new algorithm for the fast detection of communities across scales using a local criterion. We exploit the local aspect of the criterion to enable parallel computation and improve the algorithm's efficiency further. The algorithm is tested against large generated multi-scale networks and experiments demonstrate its efficiency and accuracy.
Fast Multi-Scale Detection of Relevant Communities
Erwan Le Martelot,Chris Hankin
Computer Science , 2012,
Abstract: Nowadays, networks are almost ubiquitous. In the past decade, community detection received an increasing interest as a way to uncover the structure of networks by grouping nodes into communities more densely connected internally than externally. Yet most of the effective methods available do not consider the potential levels of organisation, or scales, a network may encompass and are therefore limited. In this paper we present a method compatible with global and local criteria that enables fast multi-scale community detection. The method is derived in two algorithms, one for each type of criterion, and implemented with 6 known criteria. Uncovering communities at various scales is a computationally expensive task. Therefore this work puts a strong emphasis on the reduction of computational complexity. Some heuristics are introduced for speed-up purposes. Experiments demonstrate the efficiency and accuracy of our method with respect to each algorithm and criterion by testing them against large generated multi-scale networks. This study also offers a comparison between criteria and between the global and local approaches.
The Emory Center for Injury Control: Vision and Priorities for Reducing Violence and Injuries through Interdisciplinary Collaborations
Houry, Debra,Hankin, Abigail,Swahn, Monica
Western Journal of Emergency Medicine : Integrating Emergency Care with Population Health , 2010,
Abstract:
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