Academic literature on the topic 'Fleming-Viot processes'
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Journal articles on the topic "Fleming-Viot processes":
Hiraba, Seiji. "Jump-type Fleming-Viot processes." Advances in Applied Probability 32, no. 1 (March 2000): 140–58. http://dx.doi.org/10.1239/aap/1013540027.
Hiraba, Seiji. "Jump-type Fleming-Viot processes." Advances in Applied Probability 32, no. 01 (March 2000): 140–58. http://dx.doi.org/10.1017/s0001867800009812.
Vaillancourt, Jean. "Interacting Fleming-Viot processes." Stochastic Processes and their Applications 36, no. 1 (October 1990): 45–57. http://dx.doi.org/10.1016/0304-4149(90)90041-p.
XIANG, KAI-NAN, and TU-SHENG ZHANG. "SMALL TIME ASYMPTOTICS FOR FLEMING–VIOT PROCESSES." Infinite Dimensional Analysis, Quantum Probability and Related Topics 08, no. 04 (December 2005): 605–30. http://dx.doi.org/10.1142/s0219025705002177.
Feng, Shui, Byron Schmuland, Jean Vaillancourt, and Xiaowen Zhou. "Reversibility of Interacting Fleming–Viot Processes with Mutation, Selection, and Recombination." Canadian Journal of Mathematics 63, no. 1 (February 1, 2011): 104–22. http://dx.doi.org/10.4153/cjm-2010-071-1.
Cloez, Bertrand, and Marie-Noémie Thai. "Fleming-Viot processes: two explicit examples." Latin American Journal of Probability and Mathematical Statistics 13, no. 1 (2016): 337. http://dx.doi.org/10.30757/alea.v13-14.
Ethier, S. N., and Thomas G. Kurtz. "Fleming–Viot Processes in Population Genetics." SIAM Journal on Control and Optimization 31, no. 2 (March 1993): 345–86. http://dx.doi.org/10.1137/0331019.
HE, HUI. "FLEMING–VIOT PROCESSES IN AN ENVIRONMENT." Infinite Dimensional Analysis, Quantum Probability and Related Topics 13, no. 03 (September 2010): 489–509. http://dx.doi.org/10.1142/s0219025710004127.
Ethier, S. N., and Stephen M. Krone. "Comparing Fleming-Viot and Dawson-Watanabe processes." Stochastic Processes and their Applications 60, no. 2 (December 1995): 171–90. http://dx.doi.org/10.1016/0304-4149(95)00056-9.
Li, Zenghu, Tokuzo Shiga, and Lihua Yao. "A Reversibility Problem for Fleming-Viot Processes." Electronic Communications in Probability 4 (1999): 65–76. http://dx.doi.org/10.1214/ecp.v4-1007.
Dissertations / Theses on the topic "Fleming-Viot processes":
Vaillancourt, Jean Carleton University Dissertation Mathematics. "Interacting Fleming-Viot processes and related measure-valued processes." Ottawa, 1987.
Saadi, Habib. "Lambda-Fleming-Viot processes and their spatial extensions." Thesis, University of Oxford, 2011. http://ora.ox.ac.uk/objects/uuid:5e069206-e124-4b21-aec2-df7a69393038.
Silva, Telles Timóteo da. "Some contributions to population genetics via Fleming-Viot processes." Laboratório Nacional de Computação Científica, 2006. http://www.lncc.br/tdmc/tde_busca/arquivo.php?codArquivo=28.
RUGGIERO, MATTEO. "Urn-based particle processes for Fleming-Viot model in bayesian nonparametrics." Doctoral thesis, Università Bocconi, 2007. https://hdl.handle.net/11565/4051151.
Grieshammer, Max [Verfasser], and Andreas [Gutachter] Greven. "Measure representations of genealogical processes and applications to Fleming-Viot models / Max Grieshammer ; Gutachter: Andreas Greven." Erlangen : Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 2017. http://d-nb.info/1135779805/34.
Gufler, Stephan [Verfasser], Götz [Akademischer Betreuer] [Gutachter] Kersting, Anton [Gutachter] Wakolbinger, and Gall Jean-François [Gutachter] Le. "Tree-valued Fleming-Viot processes : a generalization, pathwise constructions, and invariance principles / Stephan Gufler ; Gutachter: Götz Kersting, Anton Wakolbinger, Jean-François Le Gall ; Betreuer: Götz Kersting." Frankfurt am Main : Universitätsbibliothek Johann Christian Senckenberg, 2017. http://d-nb.info/1126577634/34.
Straulino, Daniel. "Selection in a spatially structured population." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:3a20f7a3-27cd-4cbb-9e88-7ebb21ce4e0d.
Silva, Telles Timóteo da. "Contribuições à genética populacional via processos de Fleming-Viot." Laboratório Nacional de Computação Científica, 2006. https://tede.lncc.br/handle/tede/59.
O processo de Fleming-Viot é um processo de Markov cujo espaço de estado é um conjunto de medidas de propabilidade. As funções-amostras do processo representam as prováveis possibilidades de transformação das freqüencias de tipos genéticos presentes numa população ao longo do tempo. Obtido como solução de um problema de martingala bem posto para um operador linear construído de forma a modelar diversas características importantes no estudo da genética populacional, como mutação, seleção, deriva genética, entre outras, o processo de Fleming-Viot permite, por meio de uma abordagem matemática unificadora, tratar problemas de complexidade variada. No presente trabalho, estudamos s processs de Fleming-Viot com saltos, introduzidos por Hiraba. Interpretamos biologicamente esse saltos como mudanças abruptas que podem ocorrer, num curto espaço de tempo, durante a evolução de uma população de indivíduos, causadas por epidemias, desastres naturais ou outras catástrofes, e que levam a descontinuidades nas frequências dos tipos gênicos. Apresentamos uma forma de incluir um fator de seleção no processo com saltos, através da aplicação de uma transformação de medida do tipo Girsanov. Em seguida, fazemos uma análise do comportamento assintótico do processo utilizando técnicas de dualidade e acoplamento.
Hass, Vincent. "Modèles individu-centrés en dynamiques adaptatives, comportement asymptotique et équation canonique : le cas des mutations petites et fréquentes." Electronic Thesis or Diss., Université de Lorraine, 2023. http://www.theses.fr/2023LORR0165.
Adaptive dynamics theory is a branch of evolutionary biology which studies the links between ecology and evolution. The biological assumptions that define its framework are those of rare and small mutations and large asexual populations. Adaptive dynamics models describe the population at the level of individuals, which are characterised by their phenotypes, and aim to study the influence of heredity, mutation and selection mechanisms on the long term evolution of the population. The success of this theory comes in particular from its ability to provide a description of the long term evolution of the dominant phenotype in the population as a solution to the “Canonical Equation of Adaptive Dynamics” driven by a fitness gradient, where fitness describes the possibility of mutant invasions, and is constructed from ecological parameters. Two main mathematical approaches to the canonical equation have been developed so far: an approach based on PDEs and a stochastic approach. Despite its success, the stochastic approach is criticised by biologists as it is based on a non-realistic assumption of too rare mutations. The goal of this thesis is to correct this biological controversy by proposing more realistic probabilistic models. More precisely, the aim is to investigate mathematically, under a double asymptotic of large population and small mutations, the consequences of a new biological assumption of frequent mutations on the canonical equation. The goal is to determine, from a stochastic individual-based model, the long term behaviour of the mean phenotypic trait of the population. The question we ask is reformulated into a slow-fast asymptotic analysis acting on two eco-evolutionary time scales. A slow scale corresponding to the dynamics of the mean trait, and a fast scale corresponding to the evolutionary dynamics of the centred and dilated distribution of traits. This slow-fast asymptotic analysis is based on averaging techniques. This method requires the identification and characterisation of the asymptotic behaviour of the fast component and that the latter has ergodicity properties. More precisely, the long time behaviour of the fast component is non-classical and corresponds to that of an original measure-valued diffusion which is interpreted as a centered Fleming-Viot process that is characterised as the unique solution of a certain martingale problem. Part of these results is based on a duality relation on this non-classical process and requires moment conditions on the initial data. Using coupling techniques and the correspondence between Moran's particle processes and Kingman's genealogies, we establish that the centered Fleming-Viot process satisfies an ergodicity property with exponential convergence result in total variation. The implementation of averaging methods, inspired by Kurtz, is based on compactness-uniqueness arguments. The idea is to prove the compactness of the laws of the couple made up of the slow component and the occupation measure of the fast component and then to establish a martingale problem for all accumulation points of the family of laws of this couple. The last step is to identify these accumulation points. This method requires in particular the introduction of stopping times to control the moments of the fast component and to prove that they tend to infinity using large deviation arguments, to reduce the problem initially posed on the real line to the torus case in order to prove compactness, to identify the limit of the fast component by adapting an argument based on Dawson duality, to identify the limit of the slow component and then to move from the torus to the real line
Foucart, Clément. "Coalescents distingués échangeables et processus de Fleming-Viot généralisés avec immigration." Paris 6, 2012. http://www.theses.fr/2012PA066187.
Books on the topic "Fleming-Viot processes":
Dawson, Donald A., and Andreas Greven. Spatial Fleming-Viot Models with Selection and Mutation. Springer London, Limited, 2013.
Dawson, Donald A., Andreas Greven, and Jean Vaillancourt. Equilibria and Quasiequilibria for Infinite Collections of Interacting Fleming-Viot Processes. Amer Mathematical Society, 2003.
Book chapters on the topic "Fleming-Viot processes":
Perkins, Edwin A. "Conditional Dawson—Watanabe Processes and Fleming—Viot Processes." In Seminar on Stochastic Processes, 1991, 143–56. Boston, MA: Birkhäuser Boston, 1992. http://dx.doi.org/10.1007/978-1-4612-0381-0_12.
Ethier, S. N., and Tokuzo Shiga. "A Fleming-Viot Process with Unbounded Selection, II." In Markov Processes and Controlled Markov Chains, 305–22. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4613-0265-0_17.
Dawson, Donald A., and Vladimir Vinogradov. "Mutual Singularity of Genealogical Structures of Fleming-Viot and Continuous Branching Processes." In The Dynkin Festschrift, 61–83. Boston, MA: Birkhäuser Boston, 1994. http://dx.doi.org/10.1007/978-1-4612-0279-0_2.
Conference papers on the topic "Fleming-Viot processes":
Fragoso, M. D., and T. T. da Silva. "A note on jump-type Fleming-Viot processes." In 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601). IEEE, 2004. http://dx.doi.org/10.1109/cdc.2004.1429402.