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- E. Bacry, S. Delattre, M. Hoffmann, J. F. Muzy
- 2011

We prove a law of large numbers and a functional central limit theorem for multivariate Hawkes processes observed over a time interval [0, T ] in the limit T → ∞. We further exhibit the asymptotic behaviour of the covariation of the increments of the components of a multivariate Hawkes process, when the observations are imposed by a discrete scheme with… (More)

- E. Bacry, S. Delattre, M. Hoffmann, J. F. Muzy
- 2011

We introduce a new stochastic model for the variations of asset prices at the tick-by-tick level in dimension 1 (for a single asset) and 2 (for a pair of assets). The construction is based on marked point processes and relies on mutually exciting stochastic intensities as introduced by Hawkes. We associate a counting process with the positive and negative… (More)

We model the growth of a cell population by a piecewise deter-ministic Markov branching tree. Each cell splits into two offsprings at a division rate B(x) that depends on its size x. The size of each cell grows exponentially in time, at a rate that varies for each individual. We show that the mean empirical measure of the model satisfies a… (More)

- E. Bacry, S. Delattre, M. Hoffmann
- 2010

We introduce a new stochastic model for the variations of asset prices at the tick-by-tick level in dimension 1 (for a single asset) and 2 (for a pair of assets). The construction is based on marked point processes and relies on linear self and mutually exciting stochastic intensities as introduced by Hawkes. We associate a counting process with the… (More)

- Lydia Robert, Marc Hoffmann, Nathalie Krell, Stéphane Aymerich, Jérôme Robert, Marie Doumic
- BMC Biology
- 2013

Many organisms coordinate cell growth and division through size control mechanisms: cells must reach a critical size to trigger a cell cycle event. Bacterial division is often assumed to be controlled in this way, but experimental evidence to support this assumption is still lacking. Theoretical arguments show that size control is required to maintain size… (More)

- Stephane Boeuf, Tanja Throm, +9 authors Wiltrud Richter
- Acta biomaterialia
- 2012

Hydrophobins are fungal proteins with the ability to form immunologically inert membranes of high stability, properties that makes them attractive candidates for orthopaedic implant coatings. Cell adhesion on the surface of such implants is necessary for better integration with the neighbouring tissue; however, hydrophobin surfaces do not mediate cell… (More)

- E. Bacry, S. Delattre, M. Hoffmann
- 2013

In the context of statistics for random processes, we prove a law of large numbers and a functional central limit theorem for multivariate Hawkes processes observed over a time interval [0, T ] when T → ∞. We further exhibit the asymptotic behaviour of the covariation of the increments of the components of a multivariate Hawkes process, when the… (More)

After an overview of our statistical approach, we recall here how a probability density can be estimated from a sample of independent identically distributed random variables by kernel estimation methods [1]. We then explain in details for each model (the Age Model and the Size Model) and each data structure (f i and s i) how we estimate the division rate… (More)

- S. Delattre, M. Hoffmann
- 2012

We consider linear inverse problems in a nonparametric statistical framework. Both the signal and the operator are unknown and subject to error measurements. We establish minimax rates of convergence under squared error loss when the operator admits a blockwise singular value decomposition (blockwise SVD) and the smoothness of the signal is measured in a… (More)

- MARC HOFFMANN, MARKUS REIß
- 2004

We study the problem of estimating the coefficients of a diffusion (X t , t ≥ 0); the estimation is based on discrete data X nn , n = 0, 1,. .. , N. The sampling frequency −1 is constant, and asymptotics are taken as the number N of observations tends to infinity. We prove that the problem of estimating both the diffusion coefficient (the volatility) and… (More)