Small time two-sided LIL behavior for Lévy processes at zero

We wish to characterize when a Lévy process X _t crosses boundaries b(t), in a two-sided sense, for small times t, where b(t) satisfies very mild conditions. An integral test is furnished for computing the value of sup _t→0|X _t |/b(t) = c. In some cases, we also specify a function b(t) in terms of the Lévy triplet, such that sup _t→0 |X _t |/b(t) = 1.     

On differential inclusions with prescribed attainable sets

In this article, the inverse problem of the differential inclusion theory is studied. For a given ε>0 and a continuous set valued map t→W(t), t∈[t₀,θ], where W(t)⊂Rⁿ is compact and convex for every t∈[t₀,θ], it is required to define differential inclusion so that the Hausdorff distance between the attainable set of the differential inclusion at the time moment t with initial set (t₀,W(t₀)) and W(t) would be less than ε for every t∈[t₀,θ].     

Interpolation for partly hidden diffusion processes

Let X_t be n-dimensional diffusion process and S_t be a smooth set-valued function. Suppose X_t is invisible when X_t∈S_t, but we can see the process exactly otherwise. Let X_t0∈S_t0 and we observe the process from the beginning till the signal reappears out of the obstacle after t₀. With this information, we evaluate the estimators for the functionals of X_t on a time interval containing t₀ where the signal is hidden. We solve related 3 PDEs in general cases. We give a generalized last exit decomposition for n-dimensional Brownian motion to evaluate its estimators. An alternative Monte Carlo method is also proposed for Brownian motion. We illustrate several examples and compare the solutions between those by the closed form result, finite difference method, and Monte Carlo simulations.     

A trivariate version of ‘Lévy's equivalence’

It is shown that the trivariate stochastic processes {(M_t−W_t, M_t, Θ_t), t ≥ 0} and {(|W_t|, L_t, T_t), t ≥ 0} have the same distributions when: W = {W_t, t ≥ 0} is a Wiener process, M_t is the maximum value attained by W over the time interval [0, t], Θ_t is the time the maximum value is attained, L_t is the local time of W at level zero and time t, and T_t is the last time W is zero in the time interval [0, t]. A straightforward proof, based on ‘Tanaka's formula, establishes this result by deriving an almost sure version of the equivalence.     

Eventually positive solutions of first order nonlinear differential equations with a deviating argument

The following first order nonlinear differential equation with a deviating argument $ x'(t) + p(t)[x(\tau (t))]^\alpha = 0 $ is considered, where α > 0, α ≠ 1, p ∈ C[t ₀; ∞), p(t) > 0 for t ≧ t ₀, τ ∈ C[t ₀; ∞), lim _t→∞ τ(t) = ∞, τ(t) < t for t ≧ t ₀. Every eventually positive solution x(t) satisfying lim _t→∞ x(t) ≧ 0. The structure of solutions x(t) satisfying lim _t→∞ x(t) > 0 is well known. In this paper we study the existence, nonexistence and asymptotic behavior of eventually positive solutions x(t) satisfying lim _t→∞ x(t) = 0.     

Conditions for the convergence in distribution of maxima of stationary normal processes

The asymptotic distribution of the maximum M_n=max_1?t?nξ_t in a stationary normal sequence ξ₁,ξ,… depends on the correlation r_t between ξ₀ and ξ_t. It is well known that if r_t log t → 0 as t → ∞ or if Σr²_t<∞, then the limiting distribution is the same as for a sequence of independent normal variables. Here it is shown that this also follows from a weaker condition, which only puts a restriction on the number of t-values for which rt log t islarge. The condition gives some insight into what is essential for this asymptotic behaviour of maxima. Similar results are obtained for a stationary normal process in continuous time.     

Stochastic integral representation of some martingales

Let {X_t} be a continuous square integrable martingale. Denote its increasing (natural) process by {A_t}. Let S_t, T_t be the left and right inverses of A_t, respectively. Then for any square integrable martingale {Y_t} defined on {X_t}, Y_t = ∝₀^tψ_sdX_s, R₀ < t < S_∞ where S_∞ = lim_t→∞S_t, R₀ = inf {t: X_t ≠ 0} provided that Y(T(t)) is σ(X(T(s)): s ? t)-measurable. All martingales are assumed to be zero at t = 0. Brownian motion and Poisson processes are considered also.     

Convergence in probability and almost sure with applications

A necessary and sufficient condition is given for the convergence in probability of a stochastic process {X_t}. Moreover, as a byproduct, an almost sure convergent stochastic process {Y_t} with the same limit as {X_t} is identified. In a number of cases {Y_t} reduces to {X_t} thereby proving a.s. convergence. In other cases it leads to a different sequence but, under further assumptions, it may be shown that {X_t} and {Y_t} are a.s. equivalent, implying that {X_t} is a.s. convergent. The method applies to a number of old and new cases of branching processes providing an unified approach. New results are derived for supercritical branching random walks and multitype branching processes in varying environment.     

On the oscillation of a second-order delay equation

The oscillatory nature of two equations (r(t) y′(t))′ + p₁(t)y(t) = f(t), (r(t) y′(t))′ + p₂(t) y(t ? τ(t))= 0, is compared when positive functions p₁ and p₂ are not “too close” or “too far apart.” Then the main theorem states that if h(t) is eventually negative and a twice continuously differentiable function which satisfies (r(t) h′(t))′ + p₁(t) h(t) ? 0, then this inequality is necessary and sufficient for every bounded solution of (r(t) y′(t))′ + p₂(t) y(t ? τ(t)) = 0 to be nonoscillatory.     

Extended Jacobson density theorem for rings with derivations and automorphisms

A deterministic version of the Itô calculus is presented. We consider a modelY _t=H(N _t ,t) with a deterministic Brownian N _t and an unknown functionH. We predictY _c from the observation {Y _t;t ∈ [a, b]}, wherea. We prove that there exists an estimatorY _t based on the observation such thatE[(? _t?Y _c)²]=O((c?b)²) asc ↓b.     

Distribution and characteristic functions for correlated complex Wishart matrices

Let A(t) be a complex Wishart process defined in terms of the M×N complex Gaussian matrix X(t) by A(t)=X(t)X(t)^H. The covariance matrix of the columns of X(t) is Σ. If X(t), the underlying Gaussian process, is a correlated process over time, then we have dependence between samples of the Wishart process. In this paper, we study the joint statistics of the Wishart process at two points in time, t₁, t₂, where t₁<t₂. In particular, we derive the following results: the joint density of the elements of A(t₁), A(t₂), the joint density of the eigenvalues of Σ^-1A(t₁),Σ^-1A(t₂), the characteristic function of the elements of A(t₁), A(t₂), the characteristic function of the eigenvalues of Σ^-1A(t₁),Σ^-1A(t₂). In addition, we give the characteristic functions of the eigenvalues of a central and non-central complex Wishart, and some applications of the results in statistics, engineering and information theory are outlined.     

A conditional dichotomy theorem for stochastic processes with independent increments

Let X(t) and Y(t) be two stochastically continuous processes with independent increments over [0, T] and Lévy spectral measures M_t and N_t, respectively, and let the “time-jump” measures M and N be defined over [0, T] × $\text{R}$?{0} by M((t₁, t₂] × A) = M_t2(A) ? M_t1(A) and N((T₁, t₂] × A) = N_t2(A) ? N_t1(A). Under the assumption that M is equivalent to N, it is shown that the measures induced on function space by X(t) and Y(t) are either equivalent or orthogonal, and necessary and sufficient conditions for equivalence are given. As a corollary a complete characterization of the set of admissible translates of such processes is obtained: a function f is an admissible translate for X(t) if and only if it is an admissible translate for the Gaussian component of X(t). In particular, if X(t) has no Gaussian component, then every nontrivial translate of X(t) is orthogonal to it.     

On the instability of differential systems with varying delay

The unstable properties of the null solution of the nonautonomous delay system x′(t)=A(t)x(t)+B(t)x(t−r₁(t))+f(t,x(t),x(t−r₂(t))) are examined; the nonconstant delays r₁, r₂ are assumed to be continuous bounded functions. The case A=constant is reviewed, where a theorem, recalling the Perron instability theorem for ordinary differential equations, is obtained.     

Self-intersection local times of random walks: exponential moments in subcritical dimensions

Fix p?>?1, not necessarily integer, with p(d ? 2)?< d. We study the p-fold self-intersection local time of a simple random walk on the lattice ${\mathbb Z^d}$ up to time t. This is the p-norm of the vector of the walker??s local times, ? _t . We derive precise logarithmic asymptotics of the expectation of exp{?? _t ||? _t || _p } for scales ?? _t >?0 that are bounded from above, possibly tending to zero. The speed is identified in terms of mixed powers of t and ?? _t , and the precise rate is characterized in terms of a variational formula, which is in close connection to the Gagliardo?CNirenberg inequality. As a corollary, we obtain a large-deviation principle for ||? _t || _p /(tr _t ) for deviation functions r _t satisfying ${t r_t\gg \mathbb E[||\ell_t||_p]}$ . Informally, it turns out that the random walk homogeneously squeezes in a t-dependent box with diameter of order ? t ^1/d to produce the required amount of self-intersections. Our main tool is an upper bound for the joint density of the local times of the walk.     

On oscillation of solutions of higher order forced functional differential inequalities

Oscillation criteria for the class of forced functional differential inequalities x(t){L_nx(t) + f(t, x(t), x[g₁(t)],…, x[g_m(t)]) ? h(t)} ? 0, for n even, and x(t){L_nx(t) ? f(t, x(t), x[g₁(t)],…, x[g_m(t)]) ? h(t)} ? 0, for n odd, are established.     

On infinite-dimensional differential equations

Differential equations ·x(t) = f(x(t), t) are exhibited in a general infinite-dimensional Banach space, failing each of the following in turn. (i) The set S_t of solution values x(t) from a given point x(0) is compact. (ii) S_t is connected. (iii) Any point on the boundary ?S_t of S_t can be reached by a solution x with x(s) ??S_s, 0 ? s ? t.     

A direct numerical procedure for the Cauchy problem for the heat equation

For the Cauchy problem, u_t = u_xx, 0 < x < 1, 0 < t ? T, u(0, t) = f(t), 0 < t ? T, u_x(0, t) = g(t), 0 < t ? T, a direct numerical procedure involving the elementary solution of υ_t = υ_xx, 0 < x, 0 < t ? T, υ_x(0, t) = g(t), 0 < t ? T, υ(x, 0) = 0, 0 < x and a Taylor's series computed from f(t) ? υ(0, t) is studied. Continuous dependence better than any power of logarithmic is obtained. Some numerical results are presented.     

Probabilistic interpretation for system of conservation law arising in adhesion particle dynamics

This Note presents a construction of a solution for the nonlinear stochastic differential equation X_t = X₀ + ∫₀^t $\text{E}$[u₀(X₀)|X_s]ds, t ≥ 0. The random variable X₀ with values in $\text{R}$ and the function u₀ are given. We denote by P_t the probability distribution of X_t and u(x, t) = $\text{E}$[u₀(X₀)|X_t = x]. We prove that (P_t, u(·, t), t ≥ 0) is a weak solution for system of conservation law arising in adhesion particle dynamics.     

The Hele-Shaw problem with surface tension in a half-plane

In this paper, we consider the Hele-Shaw problem in a 2-dimensional fluid domain Ω(t) which is constrained to a half-plane. The boundary of Ω(t) consist of two components: Γ₀(t) which lies on the boundary of the half-plane, and Γ(t) which lies inside the half-plane. On Γ(t) we impose the classical boundary conditions with surface tension, and on Γ₀(t) we prescribe the normal derivative of the fluid pressure. At the point where Γ₀(t) and Γ(t) meet, there is an abrupt change in the boundary condition giving rise to a singularity in the fluid pressure. We prove that the problem has a unique solution with smooth free boundary Γ(t) for some small time interval.