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Monte Carlo Random Walk Simulations Based on Distributed Order Differential Equations with Applications to Cell Biology

Andries, Erik, Umarov, Sabir, Steinberg, Stanly (2006)

Fractional Calculus and Applied Analysis

Mathematics Subject Classification: 65C05, 60G50, 39A10, 92C37In this paper the multi-dimensional Monte-Carlo random walk simulation models governed by distributed fractional order differential equations (DODEs) and multi-term fractional order differential equations are constructed. The construction is based on the discretization leading to a generalized difference scheme (containing a finite number of terms in the time step and infinite number of terms in the space step) of the Cauchy problem for...

Moyennes harmoniques

Fernando Alcalde Cuesta (2010)

Annales de la faculté des sciences de Toulouse Mathématiques

Nous introduisons une notion de moyenne harmonique pour une marche aléatoire sur une relation d’équivalence mesurée graphée, qui généralise la notion classique de moyenne invariante. Pour les graphages à géométrie bornée, une telle moyenne existe toujours. Nous prouvons qu’une moyenne harmonique devient invariante lorsque la marche aléatoire sur presque toute orbite jouit de bonnes propriétés asymptotiques telles que la propriété de Liouville ou la récurrence.

Multidimensional limit theorems for smoothed extreme value estimates of point processes boundaries

Ludovic Menneteau (2008)

ESAIM: Probability and Statistics

In this paper, we give sufficient conditions to establish central limit theorems and moderate deviation principle for a class of support estimates of empirical and Poisson point processes. The considered estimates are obtained by smoothing some bias corrected extreme values of the point process. We show how the smoothing permits to obtain Gaussian asymptotic limits and therefore pointwise confidence intervals. Some unidimensional and multidimensional examples are provided.

Multidimensional Models for Methodological Validation in Multifractal Analysis

R. Lopes, I. Bhouri, S. Maouche, P. Dubois, M. H. Bedoui, N. Betrouni (2008)

Mathematical Modelling of Natural Phenomena

Multifractal analysis is known as a useful tool in signal analysis. However, the methods are often used without methodological validation. In this study, we present multidimensional models in order to validate multifractal analysis methods.

Multifractal properties of the sets of zeroes of Brownian paths

Dmitry Dolgopyat, Vadim Sidorov (1995)

Fundamenta Mathematicae

We study Brownian zeroes in the neighborhood of which one can observe a non-typical growth rate of Brownian excursions. We interpret the multifractal curve for the Brownian zeroes calculated in [6] as the Hausdorff dimension of certain sets. This provides an example of the multifractal analysis of a statistically self-similar random fractal when both the spacing and the size of the corresponding nested sets are random.

Multifractional processes with random exponent.

Antoine Ayache, Murad S. Taqqu (2005)

Publicacions Matemàtiques

Multifractional Processes with Random Exponent (MPRE) are obtained by replacing the Hurst parameter of Fractional Brownian Motion (FBM) with a stochastic process. This process need not be independent of the white noise generating the FBM. MPREs can be conveniently represented as random wavelet series. We will use this type of representation to study their Hölder regularity and their self-similarity.

Multiparameter multifractional brownian motion : local nondeterminism and joint continuity of the local times

Antoine Ayache, Narn-Rueih Shieh, Yimin Xiao (2011)

Annales de l'I.H.P. Probabilités et statistiques

By using a wavelet method we prove that the harmonisable-type N-parameter multifractional brownian motion (mfBm) is a locally nondeterministic gaussian random field. This nice property then allows us to establish joint continuity of the local times of an (N, d)-mfBm and to obtain some new results concerning its sample path behavior.

Multiparameter pointwise ergodic theorems for Markov operators on L∞.

Ryotaro Sato (1994)

Publicacions Matemàtiques

Let P1, ..., Pd be commuting Markov operators on L∞(X,F,μ), where (X,F,μ) is a probability measure space. Assuming that each Pi is either conservative or invertible, we prove that for every f in Lp(X,F,μ) with 1 ≤ p < ∞ the averagesAnf = (n + 1)-d Σ0≤ni≤n P1n1 P2n2 ... Pdnd f (n ≥ 0)converge almost everywhere if and only if there exists an invariant and equivalent finite measure λ for which the Radon-Nikodym derivative v = dλ/dμ is in the dual space Lp'(X,F,μ). Next we study the case in...

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