On the construction of multivariate (pre)wavelets

A new approach for the construction of wavelets and prewavelets onR ^d from multiresolution is presented. The method uses only properties of shift-invariant spaces and orthogonal projectors fromL ₂(R ^d ) onto these spaces, and requires neither decay nor stability of the scaling function. Furthermore, this approach allows a simple derivation of previous, as well as new, constructions of wavelets, and leads to a complete resolution of questions concerning the nature of the intersection and the union of a scale of spaces to be used in a multiresolution.     

Approximating average parameters of graphs

Inspired by Feige (36th STOC, 2004), we initiate a study of sublinear randomized algorithms for approximating average parameters of a graph. Specifically, we consider the average degree of a graph and the average distance between pairs of vertices in a graph. Since our focus is on sublinear algorithms, these algorithms access the input graph via queries to an adequate oracle. We consider two types of queries. The first type is standard neighborhood queries (i.e., what is the ith neighbor of vertex v?), whereas the second type are queries regarding the quantities that we need to find the average of (i.e., what is the degree of vertex v? and what is the distance between u and v?, respectively). Loosely speaking, our results indicate a difference between the two problems: For approximating the average degree, the standard neighbor queries suffice and in fact are preferable to degree queries. In contrast, for approximating average distances, the standard neighbor queries are of little help whereas distance queries are crucial. © 2008 Wiley Periodicals, Inc. Random Struct. Alg., 2008     

Numerical studies of a nonlinear heat equation with square root reaction term

Interest in calculating numerical solutions of a highly nonlinear parabolic partial differential equation with fractional power diffusion and dissipative terms motivated our investigation of a heat equation having a square root nonlinear reaction term. The original equation occurs in the study of plasma behavior in fusion physics. We begin by examining the numerical behavior of the ordinary differential equation obtained by dropping the diffusion term. The results from this simpler case are then used to construct nonstandard finite difference schemes for the partial differential equation. A variety of numerical results are obtained and analyzed, along with a comparison to the numerics of both standard and several nonstandard schemes. © 2008 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq, 2009     

‘Post‐financial meltdown: What do the services industries need from us now?’ by Roger W. Hoerl and Ronald D. Snee: Discussion 2

Hoerl and Snee have done three important things in their excellent paper. First of all, they address the current work environment conditions head‐on, describing the facts about the 2008 economic meltdown. Secondly, they provide a retrospective about the role of Statistics and Statisticians in service industries, thus providing a context for their third contribution, which is to lay out a clear road map with specific recommendations. This discussion paper expands their comments addressing the question they posed, namely ‘what do the service industries need from us now?’ It will discuss some aspects of the causes of the economic meltdown and present some methodological implications. It will then take a wide‐angle view of the role of Statistics and Statisticians in business and industry and finally, revisit the recommendations of Hoerl and Snee with some add‐ons and emphasis. Copyright © 2009 John Wiley & Sons, Ltd.     

New upper solution bounds of the discrete algebraic Riccati matrix equation

In this note, we present upper matrix bounds for the solution of the discrete algebraic Riccati equation (DARE). Using the matrix bound of Theorem 2.2, we then give several eigenvalue upper bounds for the solution of the DARE and make comparisons with existing results. The advantage of our results over existing upper bounds is that the new upper bounds of Theorem 2.2 and Corollary 2.1 are always calculated if the stabilizing solution of the DARE exists, whilst all existing upper matrix bounds might not be calculated because they have been derived under stronger conditions. Finally, we give numerical examples to demonstrate the effectiveness of the derived results.