This result has an application to the hyperbolic subset of the p-adic Mandelbrot set, whose complex analogue has been much studied [2, 4, 5, e.g.]. Much of the proof of (2) is an analysis of the Galois tower formed by the splitting fields of iterates of y2+x ∈ Fp(x)[y]. Similar towers have been studied recently by Morton [7], Odoni [8], and Aitken, Hajir, and Maire [1]. I introduce a stochastic...

If X(t) is a stochastic process taking values in some space 9C and g is a real-valued function on 9C then we may consider the process g(X(t)). Often from some knowledge about the process X(t) and the function g one can deduce properties of the process g(X(t)). For example: if X(t) is Brownian motion in R" and g is a subharmonic function on Rn that doesn't grow too fast then g(X(t)) is a semimar...

A method of moment inequalities is used to derive the principle of minimum growth rate in multiplicatively interacting stochastic processes(MISPs). When a value of a power-law exponent at the tail of probability distribution function exists in a range 0 < s ≤ 1, a first-order moment diverges and an equality for a growth rate of systems breaks down. From the estimate of inequalities, we newly fi...

Here, the driving process B is a (semi)martingale (for instance, a Brownian motion), and φ is a stochastic process satisfying suitable measurability and integrability conditions. This observation has been used by various authors as the starting point of a theory of stochastic integration for vector-valued processes. Let X be a Banach space. In [5] we characterized the class of functions φ : (0,...

We consider partial orderings for stochastic processes induced by expectations of convex or increasing convex (concave or increasing concave) functionals. We prove that these orderings are implied by the analogous finite dimensional orderings.

The subject of this paper is determining optimal replacement decisions for components under stochastic deterioration. Using the discrete renewal theorem, three cost-based criteria for comparing maintenance decisions over unbounded horizons are determined in Sec. 2: (i) the average costs per unit time, (ii) the discounted costs over an unbounded horizon, and (iii) the equivalent average costs pe...

We analyze the Gaussian approximation as a method to obtain the first and second moments of a stochastic process described by a master equation. We justify the use of this approximation with ideas coming from van Kampen’s expansion approach (the fact that the probability distribution is Gaussian at first order). We analyze the scaling of the error with a large parameter of the system and compar...

My research lies in the intersection of three fields of mathematics: stochastic processes, representation theory and the theory of Lie groups; in particular, Lévy processes in nilpotent Lie groups. In Euclidean space, these processes are generated by a particularly nice class of operator, referred to as a pseudo-differential operator. These operators have traditionally been of interest in the s...

Multivariate COGARCH(1,1) processes are introduced as a continuous-time models for multidimensional heteroskedastic observations. Our model is driven by a single multivariate Lévy process and the latent timevarying covariance matrix is directly specified as a stochastic process in the positive semidefinite matrices. After defining the COGARCH(1,1) process, we analyze its probabilistic propertie...