Comparison theorems of Hille-Wintner type for dynamic equations on time scales

We obtain an analogue of the Hille-Wintner comparison theorem for the nonoscillation of second-order linear dynamic equations on time scales. Several examples are given including applications to difference equations.

     

A Model for Studying Display Methods of Statistical Graphics

Abstract

A method of statistical graphics consists of two parts: a selection of statistical information to be displayed and a selection of a visual display method to encode the information. Some display methods lead to efficient, accurate visual decoding of encoded information, and others lead to inefficient, inaccurate decoding. It is only through rigorous studies of visual decoding that informed judgments can be made about how to choose display methods. A model has been developed to provide a framework for the study of visual decoding. The model consists of three parts: (1) a two-way classification of information on displays—quantitative-scale, quantitative-physical, categorical-scale, and categorical-physical; (2) a division of the visual processing of graphical displays into pattern perception and table look-up; (3) a specification of visual operations that are employed to carry out pattern perception and table look-up. Display methods are assessed by studying the visual operations to which they lead. Studies use the theory and experimental technique of various areas of vision research including psychophysics, cognitive psychology, and computational vision. This process is illustrated by studies of three display methods: visual reference grids for graphs with juxtaposed panels and common scales, encoding a categorical variable on a scatterplot by the type of plotting symbol, and choosing the aspect ratio of a factor-response graph.     

Measurement errors in multivariate measurement scales

Our aim is to construct a general measurement framework for analyzing the effects of measurement errors in multivariate measurement scales. We define a measurement model, which forms the core of the framework. The measurement scales in turn are often produced by methods of multivariate statistical analysis. As a central element of the framework, we introduce a new, general method of estimating the reliability of measurement scales. It is more appropriate than the classical procedures, especially in the context of multivariate analyses. The framework provides methods for various topics related to the quality of measurement, such as assessing the structural validity of the measurement model, estimating the standard errors of measurement, and correcting the predictive validity of a measurement scale for attenuation. A proper estimate of reliability is a requisite in each task. We illustrate the idea of the measurement framework with an example based on real data.     

Trees and Ehrenfeucht–Fraïssé games

Trees are natural generalizations of ordinals and this is especially apparent when one tries to find an uncountable analogue of the concept of the Scott-rank of a countable structure. The purpose of this paper is to introduce new methods in the study of an ordering between trees whose analogue is the usual ordering between ordinals. For example, one of the methods is the tree-analogue of the successor operation on the ordinals.     

The Use of an Analogue Computer in Some Operational Research Problems

Some of the basic characteristics of analogue computers are summarized and previous applications in the operational research field are reviewed. The paper briefly reports on four investigations which the authors carried out using an analogue computer: (1) Study of an inventory system; (2) Analysis of forecasting methods; (3) Locating a warehouse or distribution depot; (4) Controlling and resetting policies for processes subject to trend.     

Pontryagin’s maximum principle for dynamic systems on time scales

In this work, an analogue of Pontryagin’s maximum principle for dynamic equations on time scales is given, combining the continuous and the discrete Pontryagin maximum principles and extending them to other cases ‘in between’. We generalize known results to the case when a certain set of admissible values of the control is not necessarily closed (but convex) and the attainable set is not necessarily convex. At the same time, we impose an additional condition on the graininess of the time scale. For linear systems, sufficient conditions in the form of the maximum principle are obtained.     

Allocating fixed costs and common revenue via data envelopment analysis

An issue of considerable importance involves the allocation of fixed costs or common revenue among a set of competing entities in an equitable way. Based on the data envelopment analysis (DEA) theory, this paper proposes new methods for (i) allocating fixed costs to decision making units (DMUs) and (ii) distributing common revenue among DMUs, in such a way that the relative efficiencies of all DMUs remain unchanged and the allocations should reflect the relative efficiencies and the input-output scales of individual DMUs. To illustrate our methods, numerical results for an example are described in this paper.     

Bounds for a multivariate extension of range over standard deviation based on the Mahalanobis distance

The range over standard deviation of a set of univariate data points is given a natural multivariate extension through the Mahalanobis distance. The problem of finding extrema of this multivariate extension of “range over standard deviation” is investigated. The supremum (maximum) is found using Lagrangian methods and an interval is given for the infinimum. The independence of optimizing the Mahalanobis distance and the multivariate extension of range is demonstrated and connections are explored in several examples using an analogue of the “hat” matrix of linear regression.     

Multiscale Analysis and Data Networks

The empirical finding of self-similarity in data network traffic over many time scales motivates the need for analysis tools that are particularly well adapted for identifying structures in network traffic. These structures span a range of time scales or are scale-dependent. Wavelet-based scaling analysis methods are especially successful, both collecting summary statistics from scale to scale and probing the local structure of packet traces. They include both spectral density estimation to identify large time-scale features and multifractal estimation for small time-scale bursts. While these methods are primarily statistical in nature, we may also adapt them to visualize the “burstiness” or the instantaneous scaling features of network traffic. This expository paper discusses the theoretical and implementation issues of wavelet-based scaling analysis for network traffic. Because data network traffic research does not consist solely of analysis, we show how these wavelet-based methods may be used to monitor and infer network properties (in conjunction with on-line algorithms and careful network experimentation). More importantly, we address what types of networking questions we can and cannot investigate with such tools.     

含噪音高频数据动态整合估计波动率的方法

时间域和状态域方法是两种常见的非参数估计方法.前者主要使用的是最近的历史数据,而后者则主要依赖于过去的历史信息.本文在时间域上,通过对含噪音高频数据采用双时间尺度方法获得其波动率,进而获得经动态整合后的波动率.     

Boundary value problems with global projection conditions

Parametrices of elliptic boundary value problems for differential operators belong to an algebra of pseudodifferential operators with the transmission property at the boundary. However, generically, smooth symbols on a manifold with boundary do not have this property, and several interesting applications require a corresponding more general calculus. We introduce here a new algebra of boundary value problems that contains Shapiro-Lopatinskij elliptic as well as global projection conditions; the latter ones are necessary, if an analogue of the Atiyah-Bott obstruction does not vanish. We show that every elliptic operator admits (up to a stabilisation) elliptic conditions of that kind. Corresponding boundary value problems are then Fredholm in adequate scales of spaces. Moreover, we construct parametrices in the calculus.     

The Visual Design and Control of Trellis Display

Abstract

Trellis display is a framework for the visualization of data. Its most prominent aspect is an overall visual design, reminiscent of a garden trelliswork, in which panels are laid out into rows, columns, and pages. On each panel of the trellis, a subset of the data is graphed by a display method such as a scatterplot, curve plot, boxplot, 3-D wireframe, normal quantile plot, or dot plot. Each panel shows the relationship of certain variables conditional on the values of other variables. A number of display methods employed in the visual design of Trellis display enable it to succeed in uncovering the structure of data even when the structure is quite complicated. For example, Trellis display provides a powerful mechanism for understanding interactions in studies of how a response depends on explanatory variables. Three examples demonstrate this; in each case, we make important discoveries not appreciated in the original analyses. Several control methods are also essential to Trellis display. A control method is a technique for specifying information so that a display can be drawn. The control methods of Trellis display form a basic conceptual framework that can be used in designing software. We have demonstrated the viability of the control methods by implementing them in the S/S-PLUS system for graphics and data analysis, but they can be implemented in any software system with a basic capability for drawing graphs.     

Webb’s conjecture for fusion systems

We give a short and conceptual proof of Webb’s conjecture. Our methods are general enough to prove an analogue of the conjecture for saturated fusion systems. The author was supported by an EPSRC grant EP/D506484/1.     

Decomposition of projective spaces defined by unit-regular jordan pairs

An analogue of the Bialynicki-Birula decomposition of a smooth algebraic variety under an action of the multiplicative group is shown to hold for spaces obtained from Jordan pairs by projective equivalence. The methods are Jordan-theoretic rather than algebraic-geometric and involve unit-regularity and rank functions for Jordan pairs.     

Kolmogorov Type Law of the Logarithm for Arrays

In this paper, we establish the analogue of Kolmogorov-type law of the logarithm for an array of independent random variables. The main methods are to develop the classic Bernstein’s and Kolmogorov’s inequality and replace the boundedness condition by conditions on the cumulant transform.     

Tensor train rank minimization with hybrid smoothness regularization for visual data recovery

Recently, the tensor train (TT) rank has received much attention for tensor completion, due to its ability to explore the global low-rankness of tensors. However, existing methods still leave room for improvement, since the low-rankness itself is generally not sufficient to recover the underlying data. Inspired by this, we consider a novel tensor completion model by simultaneously exploiting the global low-rankness and local smoothness of visual data. In particular, we use low-rank matrix factorization to characterize the global TT low-rankness, and framelet and total variation regularization to enhance the local smoothness. We develop an efficient proximal alternating minimization algorithm to solve the proposed new model with guaranteed convergence. Extensive experiments on various data demonstrated that the proposed method outperforms compared methods in terms of visual and quantitative measures.     

Oscillation of even order nonlinear delay dynamic equations on time scales

One of the important methods for studying the oscillation of higher order differential equations is to make a comparison with second order differential equations. The method involves using Taylor’s Formula. In this paper we show how such a method can be used for a class of even order delay dynamic equations on time scales via comparison with second order dynamic inequalities. In particular, it is shown that nonexistence of an eventually positive solution of a certain second order delay dynamic inequality is sufficient for oscillation of even order dynamic equations on time scales. The arguments are based on Taylor monomials on time scales.     

Global Symplectic Polynomial Approximation of Area-Preserving Maps

Different methods are proposed and tested for transforming a nonlinear differential system, and more particularly a Hamiltonian one, into a map without having to integrate the whole orbit as in the well known Poincaré map technique . We construct a synthetic map, based on a global fitting, which satisfies the symplectic condition. Taking the Standard Map as a model problem we point our attention on methods suitable for comparing the model map and its synthetic counterpart. We test the agreement of the fitting on finer scales through the visual representation, the computation of the rotation number and the measure of the local distribution of the Lyapunov characteristic exponents. Comparing these results with those obtained by Froeschlé and Petit using a method based on Taylor interpolation, we show that the symplectic character is a crucial condition for the recovering of the finest details of a dynamical system. On the other hand the global character of our method makes the generalization to any system of differential equations difficult.     

Multiscale kernels

This paper reconstructs multivariate functions from scattered data by a new multiscale technique. The reconstruction uses standard methods of interpolation by positive definite reproducing kernels in Hilbert spaces. But it adopts techniques from wavelet theory and shift-invariant spaces to construct a new class of kernels as multiscale superpositions of shifts and scales of a single compactly supported function φ. This means that the advantages of scaled regular grids are used to construct the kernels, while the advantages of unrestricted scattered data interpolation are maintained after the kernels are constructed. Using such a multiscale kernel, the reconstruction method interpolates at given scattered data. No manipulations of the data (e.g., thinning or separation into subsets of certain scales) are needed. Then, the multiscale structure of the kernel allows to represent the interpolant on regular grids on all scales involved, with cheap evaluation due to the compact support of the function φ, and with a recursive evaluation technique if φ is chosen to be refinable. There also is a wavelet-like data reduction effect, if a suitable thresholding strategy is applied to the coefficients of the interpolant when represented over a scaled grid. Various numerical examples are presented, illustrating the multiresolution and data compression effects.     

Band-Limited Localized Parseval Frames and Besov Spaces on Compact Homogeneous Manifolds

In the last decade, methods based on various kinds of spherical wavelet bases have found applications in virtually all areas where analysis of spherical data is required, including cosmology, weather prediction, and geodesy. In particular, the so-called needlets (= band-limited Parseval frames) have become an important tool for the analysis of Cosmic Microwave Background (CMB) temperature data. The goal of the present paper is to construct band-limited and highly localized Parseval frames on general compact homogeneous manifolds. Our construction can be considered as an analogue of the well-known φ-transform on Euclidean spaces.