Fractional Lévy Processes as a Result of Compact Interval Integral Transformation

Fractional Brownian motion can be represented as an integral of a deterministic kernel w.r.t. an ordinary Brownian motion either on infinite or compact interval. In previous literature fractional Lévy processes are defined by integrating the infinite interval kernel w.r.t. a general Lévy process. In this article we define fractional Lévy processes using the com pact interval representation.

We prove that the fractional Lévy processes presented via different integral transformations have the same finite dimensional distributions if and only if they are fractional Brownian motions. Also, we present relations between different fractional Lévy processes and analyze the properties of such processes. A financial example is introduced as well.     

Multivariate moment based extreme value index estimators

Modeling extreme events is of paramount importance in various areas of science—biostatistics, climatology, finance, geology, and telecommunications, to name a few. Most of these application areas involve multivariate data. Estimation of the extreme value index plays a crucial role in modeling rare events. There is an affine invariant multivariate generalization of the well known Hill estimator—the separating Hill estimator. However, the Hill estimator is only suitable for heavy tailed distributions. As in the case of the separating multivariate Hill estimator, we consider estimation of the extreme value index under the assumptions of multivariate ellipticity and independent identically distributed observations. We provide affine invariant multivariate generalizations of the moment estimator and the mixed moment estimator. These estimators are suitable for both light and heavy tailed distributions. Asymptotic properties of the new extreme value index estimators are derived under multivariate elliptical distribution with known location and scatter. The effect of replacing true location and scatter by estimates is examined in a thorough simulation study. We also consider two data examples: one financial application and one meteorological application.     

On spaces which are linearly D

We introduce a generalization of D-spaces, which we call linearly D-spaces. The following results are obtained for a T₁-space X.

– X is linearly Lindelöf if, and only if, X is a linearly D-space of countable extent.

– X is linearly D provided that X is submetaLindelöf.

– X is linearly D provided that X is the union of finitely many linearly D-subspaces.

– X is compact provided that X is countably compact and X is the union of countably many linearly D-subspaces.

A New Table of Binary/Ternary Mixed Covering Codes

A table of upper bounds for K3,2(n1,n2;R), the minimum number of codewords in a covering code with n1 ternary coordinates, n2 binary coordinates, and covering radius R, in the range n = n1 + n2 13, R 3, is presented. Explicit constructions of codes are given to prove the new bounds and verify old bounds. These binary/ternary covering codes can be used as systems for the football pool game. The results include a new binary code with covering radius 1 proving K2(13,1) 736, and the following upper bound for the football pool problem for 9 matches: K3(9,1) 1356.     

Equations containing locally Henstock-Kurzweil integrable functions

A fixed point theorem in ordered spaces and a recently proved monotone convergence theorem are applied to derive existence and comparison results for solutions of a functional integral equation of Volterra type and a functional impulsive Cauchy problem in an ordered Banach space. A novel feature is that equations contain locally Henstock-Kurzweil integrable functions.     

Parameter estimation in stochastic differential equations with Markov chain Monte Carlo and non-linear Kalman filtering

This paper is concerned with parameter estimation in linear and non-linear Itô type stochastic differential equations using Markov chain Monte Carlo (MCMC) methods. The MCMC methods studied in this paper are the Metropolis–Hastings and Hamiltonian Monte Carlo (HMC) algorithms. In these kind of models, the computation of the energy function gradient needed by HMC and gradient based optimization methods is non-trivial, and here we show how the gradient can be computed with a linear or non-linear Kalman filter-like recursion. We shall also show how in the linear case the differential equations in the gradient recursion equations can be solved using the matrix fraction decomposition. Numerical results for simulated examples are presented and discussed in detail.     

Synthesis, reactivity, and computational analysis of halophosphines supported by dianionic guanidinate ligands

The reported chemistry and reactivity of guanidinate supported group 15 elements in the +3 oxidation state, particularly phosphorus, is limited when compared to their ubiquity in supporting metallic elements across the periodic table. We have synthesized a series of chlorophosphines utilizing homo- and heteroleptic (dianionic)guanidinates and have completed a comprehensive study of their reactivity. Most notable is the reluctancy of these four-membered rings to form the corresponding N-heterocyclic phosphenium cations, the tendency to chemically and thermally eliminate carbodiimide, and the scarcely observed ring expansion by insertion of a chloro(imino)phosphine into a P-N bond of the P-N-C-N framework. Computational analysis has provided corroborating evidence for the unwillingness of the halide abstraction reaction by demonstrating the exceptional electron acceptor properties of the target phosphenium cations and the underscoring strength of the P-X bond.     

Limitations of superoscillation filters in microscopy applications

The idea of superresolving pupil filters comes from the concept of superoscillations that may occur in regions of a band-limited signal with small amplitude having oscillations faster than the fastest Fourier component of the signal. In optical microscopy, superresolution can be achieved by appropriate design of pupil functions where the angular aperture determines the ultimate focal spot smaller than the Abbe diffraction limit outside the evanescent field region. The angular aperture cannot be increased indefinitely and the huge sidelobes cannot be avoided that are present in superresolving filters. The limitations of using such kind of filters in microscopy applications are discussed through computational examples.     

Manifestly non-Gaussian fluctuations in superconductor-normal metal tunnel nanostructures

We propose a mesoscopic setup which exhibits strong and manifestly non-Gaussian fluctuations of energy and temperature when suitably driven out of equilibrium. The setup consists of a normal metal island (N) coupled by tunnel junctions (I) to two superconducting leads (S), forming a SINIS structure, and is biased near the threshold voltage for quasiparticle tunneling, eV≈2Δ. The fluctuations can be measured by monitoring the time-dependent electric current through the system. This makes the setup suitable for the realization of feedback schemes which can be used to stabilize the temperature to the desired value.