Search results for " 92D10"

showing 3 items of 3 documents

Importance sampling for Lambda-coalescents in the infinitely many sites model

2011

We present and discuss new importance sampling schemes for the approximate computation of the sample probability of observed genetic types in the infinitely many sites model from population genetics. More specifically, we extend the 'classical framework', where genealogies are assumed to be governed by Kingman's coalescent, to the more general class of Lambda-coalescents and develop further Hobolth et. al.'s (2008) idea of deriving importance sampling schemes based on 'compressed genetrees'. The resulting schemes extend earlier work by Griffiths and Tavar\'e (1994), Stephens and Donnelly (2000), Birkner and Blath (2008) and Hobolth et. al. (2008). We conclude with a performance comparison o…

Class (set theory)ComputationSample (statistics)62F99 (Primary) 62P10 92D10 92D20 (Secondary)LambdaArticleSampling StudiesCoalescent theoryEvolution MolecularGene FrequencyFOS: MathematicsQuantitative Biology::Populations and EvolutionAnimalsQuantitative Biology - Populations and EvolutionEcology Evolution Behavior and Systematicscomputer.programming_languageMathematicsDiscrete mathematicsModels GeneticBETA (programming language)Probability (math.PR)Populations and Evolution (q-bio.PE)Markov ChainsGenetics PopulationPerformance comparisonFOS: Biological sciencesMutationcomputerMonte Carlo MethodMathematics - ProbabilityImportance sampling
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Probabilities of large values for sums of i.i.d. non-negative random variables with regular tail of index $-1$

2021

Let $\xi_1, \xi_2, \dots$ be i.i.d. non-negative random variables whose tail varies regularly with index $-1$, let $S_n$ be the sum and $M_n$ the largest of the first $n$ values. We clarify for which sequences $x_n\to\infty$ we have $\mathbb P(S_n \ge x_n) \sim \mathbb P(M_n \ge x_n)$ as $n\to\infty$. Outside this regime, the typical size of $S_n$ conditioned on exceeding $x_n$ is not completely determined by the largest summand and we provide an appropriate correction term which involves the integrated tail of $\xi_1$.

Mathematics::ProbabilityProbability (math.PR)FOS: Mathematics60F10 60E07 92D10Mathematics - Probability
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Analysis of DNA sequence variation within marine species using Beta-coalescents

2013

We apply recently developed inference methods based on general coalescent processes to DNA sequence data obtained from various marine species. Several of these species are believed to exhibit so-called shallow gene genealogies, potentially due to extreme reproductive behaviour, e.g. via Hedgecock's "reproduction sweepstakes". Besides the data analysis, in particular the inference of mutation rates and the estimation of the (real) time to the most recent common ancestor, we briefly address the question whether the genealogies might be adequately described by so-called Beta coalescents (as opposed to Kingman's coalescent), allowing multiple mergers of genealogies. The choice of the underlying…

Most recent common ancestorMutation ratePopulation geneticsInferenceMarine Biology62F99 (Primary) 62P10 92D10 92D20 (Secondary)Biology01 natural sciencesArticleDNA sequencingCoalescent theory010104 statistics & probability03 medical and health sciencesFOS: MathematicsAnimals0101 mathematicsQuantitative Biology - Populations and EvolutionEcology Evolution Behavior and Systematics030304 developmental biologycomputer.programming_languageMarine biology0303 health sciencesBETA (programming language)Probability (math.PR)Populations and Evolution (q-bio.PE)Sequence Analysis DNAOstreidaeEvolutionary biologyFOS: Biological sciencescomputerMathematics - Probability
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