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Limsup random fractals.

Khoshnevisan, Davar, Peres, Yuval, Xiao, Yimin (2000)

Electronic Journal of Probability [electronic only]

Local Asymptotic Normality Property for Lacunar Wavelet Series multifractal model

Jean-Michel Loubes, Davy Paindaveine (2011)

ESAIM: Probability and Statistics

We consider a lacunar wavelet series function observed with an additive Brownian motion. Such functions are statistically characterized by two parameters. The first parameter governs the lacunarity of the wavelet coefficients while the second one governs its intensity. In this paper, we establish the local and asymptotic normality (LAN) of the model, with respect to this couple of parameters. This enables to prove the optimality of an estimator for the lacunarity parameter, and to build optimal...

Local Asymptotic Normality Property for Lacunar Wavelet Series multifractal model*

Jean-Michel Loubes, Davy Paindaveine (2012)

ESAIM: Probability and Statistics

We consider a lacunar wavelet series function observed with an additive Brownian motion. Such functions are statistically characterized by two parameters. The first parameter governs the lacunarity of the wavelet coefficients while the second one governs its intensity. In this paper, we establish the local and asymptotic normality (LAN) of the model, with respect to this couple of parameters. This enables to prove the optimality of an estimator for the lacunarity parameter, and to build optimal...

Local time and related sample paths of filtered white noises

Raby Guerbaz (2007)

Annales mathématiques Blaise Pascal

We study the existence and the regularity of the local time of filtered white noises X = { X ( t ) , t [ 0 , 1 ] } . We will also give Chung’s form of the law of iterated logarithm for X , this shows that the result on the Hölder regularity, with respect to time, of the local time is sharp.

Loop-free Markov chains as determinantal point processes

Alexei Borodin (2008)

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

We show that any loop-free Markov chain on a discrete space can be viewed as a determinantal point process. As an application, we prove central limit theorems for the number of particles in a window for renewal processes and Markov renewal processes with Bernoulli noise.

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