177 research outputs found

    Higher-order Laplace equations and hyper-Cauchy distributions

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    In this paper we introduce new distributions which are solutions of higher-order Laplace equations. It is proved that their densities can be obtained by folding and symmetrizing Cauchy distributions. Another class of probability laws related to higher-order Laplace equations is obtained by composing pseudo-processes with positively-skewed Cauchy distributions which produce asymmetric Cauchy densities in the odd-order case. A special attention is devoted to the third-order Laplace equation where the connection between the Cauchy distribution and the Airy functions is obtained and analyzed.Comment: 20 pages; 5 figures; Journal of Theoretical Probabilit

    The distribution of the local time for "pseudo-processes" and its connections with fractional diffusion equations

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    We prove that the pseudoprocesses governed by heat-type equations of order n2n\geq2 have a local time in zero (denoted by L0n(t)L_{0}^{n}(t)) whose distribution coincides with the folded fundamental solution of a fractional diffusion equation of order 2(n1)/n,n22(n-1)/n,n\geq2: The distribution of L0n(t)L_{0}^{n}(t) is also expressed in terms of stable laws of order n/(n1)n/(n-1) and their form is analyzed. Furthermore, it is proved that the distribution of L0n(t)L_{0}^{n}(t) is connected with a wave equation as nn\rightarrow\infty. The distribution of the local time in zero for the pseudoprocess related to the Myiamoto’s equation is also derived and examined together with the corresponding telegraph-type fractional equation

    Bessel processes and hyperbolic Brownian motions stopped at different random times

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    Iterated Bessel processes R(gamma) (t), t > 0, gamma > 0 and their counterparts on hyperbolic spaces, i.e. hyperbolic Brownian motions B(hp)(t), t > 0 are examined and their probability laws derived. The higher-order partial differential equations governing the distributions of I(R)(t) = R(1)(gamma 1)(R(2)(gamma 2)(t)), t > 0 and J(R)(t) = R(1)(gamma 1) (R(2)(gamma 2) (t)(2)), t > 0 are obtained and discussed. Processes of the form R(gamma) (T(t)), t > 0, B(hp) (T(t)), t > 0 where T(t) = inf{s >= 0 : B(s) = t} are examined and numerous probability laws derived, including the Student law, the arcsine laws (also their asymmetric versions), the Lamperti distribution of the ratio of independent positively skewed stable random variables and others. For the random variable R(gamma)(T(t)(mu)), t > 0 (where T(t)(mu) = inf{s >= 0 : B(mu) (s) = t} and B(mu) is a Brownian motion with drift mu), the explicit probability law and the governing equation are obtained. For the hyperbolic Brownian motions on the Poincare half-spaces H(2)(+), H(3)(+) (of respective dimensions 2, 3) we study B(hp) (T(t)), t > 0 and the corresponding governing equation. Iterated processes are useful in modelling motions of particles on fractures idealized as Bessel processes (in Euclidean spaces) or as hyperbolic Brownian motions (in non-Euclidean spaces). Crown Copyright (C) 2010 Published by Elsevier B.V. All rights reserved

    On the Integral of Fractional Poisson Processes

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    In this paper we consider the Riemann--Liouville fractional integral Nα,ν(t)=1Γ(α)0t(ts)α1Nν(s)ds\mathcal{N}^{\alpha,\nu}(t)= \frac{1}{\Gamma(\alpha)} \int_0^t (t-s)^{\alpha-1}N^\nu(s) \, \mathrm ds , where Nν(t)N^\nu(t), t0t \ge 0, is a fractional Poisson process of order ν(0,1]\nu \in (0,1], and α>0\alpha > 0. We give the explicit bivariate distribution Pr{Nν(s)=k,Nν(t)=r}\Pr \{N^\nu(s)=k, N^\nu(t)=r \}, for tst \ge s, rkr \ge k, the mean ENα,ν(t)\mathbb{E}\, \mathcal{N}^{\alpha,\nu}(t) and the variance VarNα,ν(t)\mathbb{V}\text{ar}\, \mathcal{N}^{\alpha,\nu}(t). We study the process Nα,1(t)\mathcal{N}^{\alpha,1}(t) for which we are able to produce explicit results for the conditional and absolute variances and means. Much more involved results on N1,1(t)\mathcal{N}^{1,1}(t) are presented in the last section where also distributional properties of the integrated Poisson process (including the representation as random sums) is derived. The integral of powers of the Poisson process is examined and its connections with generalised harmonic numbers is discussed

    Pseudoprocesses related to space-fractional higher-order heat-type equations

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    In this paper we construct pseudo random walks (symmetric and asymmetric) which converge in law to compositions of pseudoprocesses stopped at stable subordinators. We find the higher-order space-fractional heat-type equations whose fundamental solutions coincide with the law of the limiting pseudoprocesses. The fractional equations involve either Riesz operators or their Feller asymmetric counterparts. The main result of this paper is the derivation of pseudoprocesses whose law is governed by heat-type equations of real-valued order γ>2\gamma>2. The classical pseudoprocesses are very special cases of those investigated here

    Fractional pure birth processes

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    We consider a fractional version of the classical nonlinear birth process of which the Yule--Furry model is a particular case. Fractionality is obtained by replacing the first order time derivative in the difference-differential equations which govern the probability law of the process with the Dzherbashyan--Caputo fractional derivative. We derive the probability distribution of the number Nν(t)\mathcal{N}_{\nu}(t) of individuals at an arbitrary time tt. We also present an interesting representation for the number of individuals at time tt, in the form of the subordination relation Nν(t)=N(T2ν(t))\mathcal{N}_{\nu}(t)=\mathcal{N}(T_{2\nu}(t)), where N(t)\mathcal{N}(t) is the classical generalized birth process and T2ν(t)T_{2\nu}(t) is a random time whose distribution is related to the fractional diffusion equation. The fractional linear birth process is examined in detail in Section 3 and various forms of its distribution are given and discussed.Comment: Published in at http://dx.doi.org/10.3150/09-BEJ235 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm

    Fractional diffusion equations and processes with randomly varying time

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    In this paper the solutions uν=uν(x,t)u_{\nu}=u_{\nu}(x,t) to fractional diffusion equations of order 0<ν20<\nu \leq 2 are analyzed and interpreted as densities of the composition of various types of stochastic processes. For the fractional equations of order ν=12n\nu =\frac{1}{2^n}, n1,n\geq 1, we show that the solutions u1/2nu_{{1/2^n}} correspond to the distribution of the nn-times iterated Brownian motion. For these processes the distributions of the maximum and of the sojourn time are explicitly given. The case of fractional equations of order ν=23n\nu =\frac{2}{3^n}, n1,n\geq 1, is also investigated and related to Brownian motion and processes with densities expressed in terms of Airy functions. In the general case we show that uνu_{\nu} coincides with the distribution of Brownian motion with random time or of different processes with a Brownian time. The interplay between the solutions uνu_{\nu} and stable distributions is also explored. Interesting cases involving the bilateral exponential distribution are obtained in the limit.Comment: Published in at http://dx.doi.org/10.1214/08-AOP401 the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org

    On a fractional linear birth--death process

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    In this paper, we introduce and examine a fractional linear birth--death process Nν(t)N_{\nu}(t), t>0t>0, whose fractionality is obtained by replacing the time derivative with a fractional derivative in the system of difference-differential equations governing the state probabilities pkν(t)p_k^{\nu}(t), t>0t>0, k0k\geq0. We present a subordination relationship connecting Nν(t)N_{\nu}(t), t>0t>0, with the classical birth--death process N(t)N(t), t>0t>0, by means of the time process T2ν(t)T_{2\nu}(t), t>0t>0, whose distribution is related to a time-fractional diffusion equation. We obtain explicit formulas for the extinction probability p0ν(t)p_0^{\nu}(t) and the state probabilities pkν(t)p_k^{\nu}(t), t>0t>0, k1k\geq1, in the three relevant cases λ>μ\lambda>\mu, λ<μ\lambda<\mu, λ=μ\lambda=\mu (where λ\lambda and μ\mu are, respectively, the birth and death rates) and discuss their behaviour in specific situations. We highlight the connection of the fractional linear birth--death process with the fractional pure birth process. Finally, the mean values ENν(t)\mathbb{E}N_{\nu}(t) and VarNν(t)\operatorname {\mathbb{V}ar}N_{\nu}(t) are derived and analyzed.Comment: Published in at http://dx.doi.org/10.3150/10-BEJ263 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm
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