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  Subjects -> STATISTICS (Total: 130 journals)
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Journal of Theoretical Probability
Journal Prestige (SJR): 0.981
Citation Impact (citeScore): 1
Number of Followers: 3  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1572-9230 - ISSN (Online) 0894-9840
Published by Springer-Verlag Homepage  [2467 journals]
  • Moderate Deviation Principle for Multiscale Systems Driven by Fractional
           Brownian Motion

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      Abstract: Abstract In this paper, we study the moderate deviations principle (MDP) for slow–fast stochastic dynamical systems where the slow motion is governed by small fractional Brownian motion (fBm) with Hurst parameter \(H\in (1/2,1)\) . We derive conditions on the moderate deviations scaling and on the Hurst parameter H under which the MDP holds. In addition, we show that in typical situations the resulting action functional is discontinuous in H at \(H=1/2\) , suggesting that the tail behavior of stochastic dynamical systems perturbed by fBm can have different characteristics than the tail behavior of such systems that are perturbed by standard Brownian motion.
      PubDate: 2023-01-16
       
  • Asymptotic Properties of Random Contingency Tables with Uniform Margin

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      Abstract: Abstract Let \(C\ge 2\) be a positive integer. Consider the set of \(n\times n\) non-negative integer matrices whose row sums and column sums are all equal to Cn and let \(X=(X_{ij})_{1\le i,j\le n}\) be uniformly distributed on this set. This X is called the random contingency table with uniform margin. In this paper, we study various asymptotic properties of \(X=(X_{ij})_{1\le i,j\le n}\) as \(n\rightarrow \infty \) .
      PubDate: 2023-01-09
       
  • Normal Approximation of Compound Hawkes Functionals

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      Abstract: Abstract We derive quantitative bounds in the Wasserstein distance for the approximation of stochastic integrals with respect to Hawkes processes by a normally distributed random variable. In the case of deterministic and nonnegative integrands, our estimates involve only the third moment of the integrand in addition to a variance term using a squared norm of the integrand. As a consequence, we are able to observe a “third moment phenomenon” in which the vanishing of the first cumulant can lead to faster convergence rates. Our results are also applied to compound Hawkes processes, and improve on the current literature where estimates may not converge to zero in large time or have been obtained only for specific kernels such as the exponential or Erlang kernels.
      PubDate: 2023-01-07
       
  • A Large Deviation Principle for the Stochastic Heat Equation with General
           Rough Noise

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      Abstract: Abstract We study the Freidlin–Wentzell large deviation principle for the nonlinear one-dimensional stochastic heat equation driven by a Gaussian noise: $$\begin{aligned} \frac{\partial u^{{\varepsilon }}(t,x)}{\partial t}=\frac{\partial ^2 u^{{\varepsilon }}(t,x)}{\partial x^2}+\sqrt{{\varepsilon }}\sigma (t, x, u^{{\varepsilon }}(t,x))\dot{W}(t,x),\quad t> 0,\, x\in \mathbb {R}, \end{aligned}$$ where \(\dot{W}\) is white in time and fractional in space with Hurst parameter \(H\in \left( \frac{1}{4},\frac{1}{2}\right) \) . Recently, Hu and Wang (Ann Inst Henri Poincaré Probab Stat 58(1):379–423, 2022) have studied the well-posedness of this equation without the technical condition of \(\sigma (0)=0\) which was previously assumed in Hu et al. (Ann Probab 45(6):4561–4616, 2017). We adopt a new sufficient condition proposed by Matoussi et al. (Appl Math Optim 83(2):849–879, 2021) for the weak convergence criterion of the large deviation principle.
      PubDate: 2023-01-06
       
  • Semi-uniform Feller Stochastic Kernels

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      Abstract: Abstract This paper studies transition probabilities from a Borel subset of a Polish space to a product of two Borel subsets of Polish spaces. For such transition probabilities it introduces and studies the property of semi-uniform Feller continuity. This paper provides several equivalent definitions of semi-uniform Feller continuity and establishes its preservation under integration. The motivation for this study came from the theory of Markov decision processes with incomplete information, and this paper provides the fundamental results useful for this theory.
      PubDate: 2023-01-06
       
  • Stochastic Dynamics of Generalized Planar Random Motions with Orthogonal
           Directions

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      Abstract: Abstract We study planar random motions with finite velocities, of norm \(c>0\) , along orthogonal directions and changing at the instants of occurrence of a nonhomogeneous Poisson process with rate function \(\lambda = \lambda (t),\ t\ge 0\) . We focus on the distribution of the current position \(\bigl (X(t), Y(t)\bigr ),\ t\ge 0\) , in the case where the motion has orthogonal deviations and where also reflection is admitted. In all the cases, the process is located within the closed square \(S_{ct}=\{(x,y)\in {\mathbb {R}}^2\,:\, x + y \le ct\}\) and we obtain the probability law inside \(S_{ct}\) , on the edge \(\partial S_{ct}\) and on the other possible singularities, by studying the partial differential equations governing all the distributions examined. A fundamental result is that the vector process (X, Y) is probabilistically equivalent to a linear transformation of two (independent or dependent) one-dimensional symmetric telegraph processes with rate function proportional to \(\lambda \) and velocity c/2. Finally, we extend the results to a wider class of orthogonal-type evolutions.
      PubDate: 2023-01-04
       
  • On the Probabilistic Representation of the Free Effective Resistance of
           Infinite Graphs

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      Abstract: Abstract We completely characterize when the free effective resistance of an infinite graph whose vertices have finite degrees can be expressed in terms of simple hitting probabilities of the random walk on the graph.
      PubDate: 2023-01-04
       
  • Strong Local Nondeterminism and Exact Modulus of Continuity for Isotropic
           Gaussian Random Fields on Compact Two-Point Homogeneous Spaces

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      Abstract: Abstract This paper is concerned with sample path properties of real-valued isotropic Gaussian fields on compact two-point homogeneous spaces. In particular, we establish the property of strong local nondeterminism of an isotropic Gaussian field and then exploit this result to establish an exact uniform modulus of continuity for its sample paths.
      PubDate: 2023-01-03
       
  • Selfsimilar Free Additive Processes and Freely Selfdecomposable
           Distributions

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      Abstract: Abstract In the paper by Fan (Inf Dim Anal Quant Probab Rel Topics 9:451–469, 2006), he introduced the marginal selfsimilarity of non-commutative stochastic processes and proved that the marginal distributions of selfsimilar processes with freely independent increments are freely selfdecomposable. In this paper, we firstly introduce a new definition, stronger than Fan’s in general, of selfsimilarity via linear combinations of non-commutative stochastic processes, although the two definitions are equivalent for non-commutative stochastic processes with freely independent increments. We secondly prove the converse of Fan’s result, to complete the relationship between selfsimilar free additive processes and freely selfdecomposable distributions. Furthermore, we construct stochastic integrals with respect to free additive processes for representing the background driving free Lévy processes of freely selfdecomposable distributions. A relationship between freely selfdecomposable distributions and their background driving free Lévy processes in terms of their free cumulant transforms is also given, and several examples are discussed.
      PubDate: 2022-12-29
       
  • Error distribution of the Euler approximation scheme for stochastic
           Volterra equations

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      Abstract: Abstract The purpose of this paper is to establish the convergence in distribution of the normalized error in the Euler approximation scheme for stochastic Volterra equations driven by a standard Brownian motion, with a kernel of the form \((t-s)^\alpha \) , where \(\alpha \in \left( -\frac{1}{2}, \frac{1}{2}\right) \) .
      PubDate: 2022-12-23
       
  • Limit Theorems for Deviation Means of Independent and Identically
           Distributed Random Variables

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      Abstract: Abstract We derive a strong law of large numbers, a central limit theorem, a law of the iterated logarithm and a large deviation theorem for so-called deviation means of independent and identically distributed random variables. (For the strong law of large numbers, we suppose only pairwise independence instead of (total) independence.) The class of deviation means is a special class of M-estimators or more generally extremum estimators, which are well studied in statistics. The assumptions of our limit theorems for deviation means seem to be new and weaker than the known ones for M-estimators in the literature. In particular, our results on the strong law of large numbers and on the central limit theorem generalize the corresponding ones for quasi-arithmetic means due to de Carvalho (Am Stat 70(3):270–274, 2016) and the ones for Bajraktarević means due to Barczy and Burai (Aequ Math 96(2):279–305, 2022).
      PubDate: 2022-12-23
       
  • Ergodic Theorems with Random Weights for Stationary Random Processes and
           Fields

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      Abstract: Abstract Let X(t) be an ergodic stationary random process or an ergodic homogeneous random field on \({\mathbb {R}}^m,m\ge 2\) , and let M(B) be a mixing homogeneous locally finite random Borel measure with mean density \(\gamma \) on \({\mathbb {R}}^m,m\ge 1\) . We assume that X and M are independent and possess finite expectations. If \(\{T_n\}\) is an increasing sequence of bounded convex sets, containing balls of radii \(r_n\rightarrow \infty \) , then $$\begin{aligned} \lim _{n\rightarrow \infty }\frac{1}{\lambda (T_n)}\int _{T_n}X(t)M(\textrm{d}t,w)=\gamma E[X(0)]\text { a.s. and in } L^1. \end{aligned}$$ Special cases are ergodic theorems with averages over finite random sets. Example: If S is an independent-of-X Poisson random set in \({\mathbb {R}}^m\) with mean density \(\gamma \) , then $$\begin{aligned} \lim _{n\rightarrow \infty }\frac{1}{ {\lambda (T_n)}}\sum _{t\in S \cap T_n}X(t)=\gamma E[X(0 )] \ \text {a.s. and in } L^1 \ \ (\text {card} (S\cap T_n)<\infty \ \text {a.s.}). \end{aligned}$$ These theorems offer a universal way of constructing consistent estimators using observations on finite sets.
      PubDate: 2022-12-23
       
  • Existence and Uniqueness of Solutions for Multi-dimensional Reflected
           Backward Stochastic Differential Equations with Diagonally Quadratic
           Generators

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      Abstract: Abstract In this paper, we study multi-dimensional reflected backward stochastic differential equations (BSDEs) with diagonally quadratic generators. Using the comparison theorem for diagonally quadratic BSDEs established recently in Luo (Disc Contin Dyn Syst 41(6):2543–2557, 2021), we obtain the existence and uniqueness of a solution by a penalization method. Moreover, we provide a comparison theorem.
      PubDate: 2022-12-19
       
  • Wasserstein-Type Distances of Two-Type Continuous-State Branching
           Processes in Lévy Random Environments

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      Abstract: Abstract Under natural conditions, we prove exponential ergodicity in the \( L_1\) -Wasserstein distance of two-type continuous-state branching processes in Lévy random environments with immigration. Furthermore, we express precisely the parameters of the exponent. The coupling method and the conditioned branching property play an important role in the approach. Using the tool of superprocesses, ergodicity in total variation distance is also proved.
      PubDate: 2022-12-19
       
  • Support Theorem for Lévy-driven Stochastic Differential Equations

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      Abstract: Abstract We provide a support theorem for the law of the solution to a stochastic differential equation (SDE) with jump noise. This theorem applies to quite general Lévy-driven SDEs and is illustrated by examples with rather degenerate jump noises, where the theorem leads to an informative description of the support.
      PubDate: 2022-12-17
       
  • Resolution of Sigma-Fields for Multiparticle Finite-State Action
           Evolutions with Infinite Past

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      Abstract: Abstract For multiparticle finite-state action evolutions, we prove that the observation \( \sigma \) -field admits a resolution involving a third noise which is generated by a random variable with uniform law. The Rees decomposition from semigroup theory and the theory of infinite convolutions are utilized in our proofs.
      PubDate: 2022-12-17
       
  • Using Stein’s Method to Analyze Euler–Maruyama Approximations of
           Regime-Switching Jump Diffusion Processes

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      Abstract: Abstract For a kind of regime-switching jump diffusion process \((X_t,Z_t)_{t\ge 0}\) , under some conditions, it is exponentially ergodic under the weighted total variation distance with ergodic measure \(\mu \) . We use the Euler–Maruyama scheme of the process \((X_t,Z_t)_{t\ge 0}\) which has an ergodic measure \(\mu _{\eta }\) ( \(\eta \) is the step size of the Euler–Maruyama scheme) to approximate the ergodic measure \(\mu \) . Furthermore, we use Stein’s method to prove that the convergence rate of \(\mu _{\eta }\) to \(\mu \) is \(\eta ^{\frac{1}{2}}\) in terms of some function-class distance \(d_{{\mathcal {G}}}(\mu ,\mu _{\eta })\) .
      PubDate: 2022-12-15
       
  • Equivalence–Singularity Dichotomy in Markov Measures

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      Abstract: Abstract We establish an equivalence–singularity dichotomy for a large class of one-dimensional Markov measures. Our approach is new in that we deal with one-sided and two-sided chains simultaneously and in that we do not appeal to a 0-1 law. In fact, we deduce a new 0-1 law from the dichotomy.
      PubDate: 2022-12-02
       
  • Second-Order Tail Behavior for Stochastic Discounted Value of Aggregate
           Net Losses in a Discrete-Time Risk Model

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      Abstract: Abstract Consider a discrete-time risk model, in which an insurer makes both risk-free and risky investments. Within period k, the net loss is denoted by a real-valued random variable \(X_k\) , and the stochastic discount factor is a bounded positive random variable \(Y_k\) . Assume that \((X_k,Y_k), k\in {\mathbb {N}}\) , form a sequence of independent and identically distributed random pairs following a common bivariate Farlie–Gumbel–Morgenstern distribution with marginal distributions F on \({\mathbb {R}}\) and G on [a, b], respectively, for some \(0<a\le b<\infty \) . Under the condition that F is second-order subexponential, we establish a second-order expansion for the tail probability of the stochastic discounted value of aggregate net losses. Compared with the first-order one, our second-order asymptotic result is more precise, which is demonstrated by numerical studies.
      PubDate: 2022-12-01
       
  • Higher-Order Error Estimates of the Discrete-Time Clark–Ocone
           Formula

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      Abstract: Abstract In this article, we investigate the convergence rate of the discrete-time Clark–Ocone formula provided by Akahori–Amaba–Okuma (J Theor Probab 30: 932–960, 2017). In that paper, they mainly focus on the \(L_{2}\) -convergence rate of the first-order error estimate related to the tracking error of the delta hedge in mathematical finance. Here, as two extensions, we estimate “the higher order error” for Wiener functionals with an integrability index 2 and “an arbitrary differentiability index.”
      PubDate: 2022-12-01
       
 
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