Partitioned difference families and almost difference sets

Partitioned difference families (PDFs) were first studied by Ding and Yin in conjunction with the construction of constant composition codes (CCCs). In 2008, Yin et al. presented the constructions of a number of infinite classes of PDFs based on known difference sets in GF(q). In this paper, we further investigate the constructions of PDFs by using known almost difference sets in GF(q), and establish some recursive constructions of PDFs. As their applications, we also get a number of perfect difference systems of sets (DSSs) over Z_q² with q odd prime.     

非良基集与共代数理论研究

作为经典集合论的扩张,非良基集合论具有更为丰富的集合全域。它能够提供一套完备的工具刻画现实世界中众多的循环现象。共代数是代数的对偶概念。在非良基的范畴下,使用共代数方法,可以方便地构造各种循环现象在集合理论上的模型。因此,对非良基集及共代数理论的研究极具吸引力。     

高水平数字政府建设的影响因素及推进路径

数字政府建设作为推进政府治理体系与治理能力现代化的重要战略举措,不仅是简单的技术变革问题,更是技术与治理二元叠加裂变后的信息化技术与组织、环境的深度融合发展问题。现有研究缺乏对数字政府建设差异化路径的影响因素的深入探究。以TOE为分析框架,采用NCA和fsQCA相结合的方法,从组态视角深入挖掘中国31个省(市、区)高水平数字政府建设的影响因素及推进路径。研究表明：政策驱动是数字政府建设的必要条件,是数字政府建设与发展的制度保障;高水平的数字政府建设路径存在差异化,不同影响因素的适宜组合可推动高水平数字政府建设;在特定资源要素组合下,完善技术能力、加强财政供给能力与政策驱动是快速推动数字政府建设必不可缺的条件。其研究有助于深化中国数字政府建设背后复杂的因果机制,为因地制宜打造差异化的高水平数字政府提供借鉴。     

The existence of almost difference families

Almost difference families (ADFs) were introduced by Ding and Yin as a useful generalization of almost difference sets (ADSs), and a number of infinite classes of almost difference families had been constructed. Suppose q is a prime power. To construct combinatorial designs in GF(q), one often needs to find an element xGF(q){0}, such that some polynomials in GF(q)[x] of degree one or two satisfying certain conditions. Weil's theorem on character sum estimates is very useful to do this. In this paper, a general bound for finding such x is given. By using this bound and computer searching, some known results on almost difference families by Ding and Yin are improved.     

Kolmogorov-smirnov confidence sets: the case of more than one sample

For the two-sample problem, distribution-free confidence sets for the shift parameter when the scale parameters are equal and for both the shift and the ratio of scale parameters are derived. Multiple comparisons for the k sample location problem are constructed when all scale parameters are equal. Examples are given. Procedures may be completed with only pencil and paper.

     

Application of copulas to multivariate control charts

The most popular multivariate control chart for monitoring the mean of a distribution is probably the Hotelling T² rule. Unfortunately, this rule relies on the assumption that the distribution under control is Gaussian, which is rarely true in practice. The objective of this paper is to propose a new approach for the non-normal multivariate case. It consists in the construction of a tolerance region obtained from a density level set estimation. The method follows a “plug-in” approach in which the density of the observations is previously estimated. This estimation is conducted using copulas modeling, an increasingly popular tool in multivariate modeling.     

Efficient Confidence Interval Methodologies for the Non Centrality Parameter of a Non Central t Distribution

This article considers the problem of constructing a confidence interval for the non centrality parameter of a non central t distribution. This has applications to the signal to noise ratio in regression problems and to the coefficient of variation for normally distributed data. A new procedure is developed that provides shorter confidence intervals than the standard procedure, and a program is available for its implementation. This new procedure will be useful for practitioners, and its development also provides some interesting theoretical results.     

Variable Selection for Kernel Classification

In this article, a variable selection procedure, called surrogate selection, is proposed which can be applied when a support vector machine or kernel Fisher discriminant analysis is used in a binary classification problem. Surrogate selection applies the lasso after substituting the kernel discriminant scores for the binary group labels, as well as values for the input variable observations. Empirical results are reported, showing that surrogate selection performs well.     

Stochastic ordering and a class of multivariate new better than used distributions

A new characterization for the univariate class of new better than used ‘NBU’ distributions in terms of stochastic ordering is introduced. A multivariate version of this characterization is then used to define a multivariate class of NBU distributions. Basic properties of this class are derived. Comparisons and relationships of this new class with earlier classes are developed. Two multivariate new worse than used (NWU) classes of life distributions are defined and compared and their basic properties are studied.