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Documents  Raoul, Gaël | enregistrements trouvés : 8

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Research talks;Probability and Statistics

The aim of this course is to present some examples of stochastic models suitable for population dynamics.
The first part will introduce a class of continuous time models called piecewise deterministic Markov processes (PDMPs). Their trajectories are deterministic with jumps at random times. They are especially suitable to model phenomena with different time scales: a fast time-sacla corresponding to the deterministic behaviour and a slow time-scale corresponding to the jumps. I'll present different biological systems that can be modelled by PDMPs, explain how they can be simulated.
The second part will focus on random models for cell division when the whole branching population is taken into account. I'll present two data sets from biological experiments trying to determine whether cell division is symmetric or not. I'll explain how statistic tools can help answer this question.
The aim of this course is to present some examples of stochastic models suitable for population dynamics.
The first part will introduce a class of continuous time models called piecewise deterministic Markov processes (PDMPs). Their trajectories are deterministic with jumps at random times. They are especially suitable to model phenomena with different time scales: a fast time-sacla corresponding to the deterministic behaviour and a slow ...

60Jxx ; 92Bxx ; 90Cxx

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Research schools;Probability and Statistics

The aim of this course is to present some examples of stochastic models suitable for population dynamics.
The first part will introduce a class of continuous time models called piecewise deterministic Markov processes (PDMPs). Their trajectories are deterministic with jumps at random times. They are especially suitable to model phenomena with different time scales: a fast time-sacla corresponding to the deterministic behaviour and a slow time-scale corresponding to the jumps. I'll present different biological systems that can be modelled by PDMPs, explain how they can be simulated.
The second part will focus on random models for cell division when the whole branching population is taken into account. I'll present two data sets from biological experiments trying to determine whether cell division is symmetric or not. I'll explain how statistic tools can help answer this question.
The aim of this course is to present some examples of stochastic models suitable for population dynamics.
The first part will introduce a class of continuous time models called piecewise deterministic Markov processes (PDMPs). Their trajectories are deterministic with jumps at random times. They are especially suitable to model phenomena with different time scales: a fast time-sacla corresponding to the deterministic behaviour and a slow ...

60Jxx ; 92Bxx ; 90Cxx

... Lire [+]

Déposez votre fichier ici pour le déplacer vers cet enregistrement.

Research schools;Probability and Statistics

The aim of this course is to present some examples of stochastic models suitable for population dynamics.
The first part will introduce a class of continuous time models called piecewise deterministic Markov processes (PDMPs). Their trajectories are deterministic with jumps at random times. They are especially suitable to model phenomena with different time scales: a fast time-sacla corresponding to the deterministic behaviour and a slow time-scale corresponding to the jumps. I'll present different biological systems that can be modelled by PDMPs, explain how they can be simulated.
The second part will focus on random models for cell division when the whole branching population is taken into account. I'll present two data sets from biological experiments trying to determine whether cell division is symmetric or not. I'll explain how statistic tools can help answer this question.
The aim of this course is to present some examples of stochastic models suitable for population dynamics.
The first part will introduce a class of continuous time models called piecewise deterministic Markov processes (PDMPs). Their trajectories are deterministic with jumps at random times. They are especially suitable to model phenomena with different time scales: a fast time-sacla corresponding to the deterministic behaviour and a slow ...

60Jxx ; 92Bxx ; 90Cxx

... Lire [+]

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Research talks;Partial Differential Equations;Mathematics in Science and Technology

35B40 ; 35Q20 ; 35K40 ; 35Q92 ; 35A01 ; 92D15

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Research schools;Partial Differential Equations;Mathematics in Science and Technology;Probability and Statistics

92D25 ; 35Q92 ; 60J85 ; 60H30 ; 35K57 ; 35K55

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Research schools;Partial Differential Equations;Mathematical Physics;Probability and Statistics

92D25 ; 35Q92 ; 60J85 ; 60H30 ; 35K57 ; 35K55

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Research schools;Partial Differential Equations;Mathematics in Science and Technology;Probability and Statistics

35K57 ; 92D25 ; 35Q92

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Research schools;Partial Differential Equations;Mathematics in Science and Technology;Probability and Statistics

35K57 ; 92D25 ; 35Q92

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