一类非线性算子方程组的选代求解

在Ｂａｎａｃｈ空间上，利用锥理论与迭代方法研究了一类非线性算子方程组解的再在性与唯一性，推广了文［１］的主要结果，并给出了应用。     

回归分析在短跑教学中的应用

针对教学中学生100m跑的具体情况,采用逐步回归分析方法建立了回归方程;在此基础上,分别以各相关因素、100 m跑成绩作为因变量与自变量建立了多项式回归方程,并依据正态分布理论制定了各因素平衡发展的标准.上述方法在指导短跑教学中取得了较好的效果.     

关于中值定理“中间点”的渐近性质

文［１］给出了当区间长度趋于无穷大时Ｌａｇｒａｎｇｅ中值定理＂中间点＂的渐进性质。本文首先减弱了文［１］中主要定理的条件，从而改进了文［１］中的结果，然后给出积分中值定理当区间长度趋于无穷大时＂中间点＂的渐近性质．     

中国城市民生发展的区域差异测度、来源分解与形成机理

本文基于熵值法构建城市民生发展指数,利用Dagum基尼系数和方差分解方法首次从空间和结构两个视角考察我国城市民生发展的差异大小及来源,并运用关系数据分析范式研究其形成机理。研究发现:我国城市民生发展水平持续向好,但2010年之后民生发展不均衡现象显著;民生发展总体差异主要来源于区域间差异,其中东部和中部区域间差异贡献最大,东部区域内差异贡献显著高于中部、西部地区;社会发展差异和生态建设差异是民生发展差异的主要结构来源;人民生活差异、科技创新差异对民生发展差异的影响均从东向西依次减弱,社会发展差异的作用则依次增强,生态建设差异的影响在中部地区最为突出,经济发展差异对东部地区的影响较弱;人民生活差异、科技创新差异上升是导致2010年之后民生发展差异扩大的主要原因。本研究丰富了城市民生评价体系的构建方案,为揭示我国城市民生发展差异状况、探索协同提升对策提供了重要借鉴经验。     

Asymptotic expansion of the nonnull distribution of likelihood ratio statistic for testing multisample sphericity

Asymptotic expansion of the nonnull distribution of the likelihood ratio statistic for testing muitisample sphericity in q multinormal populations is derived for the alternatives close to the null hypothesis.     

Estimation of location parameters of several exponential distributions

In this paper we address the problem of simultaneous estimation of location parameters of several exponential distributions assuming that the scale parameters are unknown and possibly unequal. From a decision theoretic point of view it is shown that the standard estimators are inadmissible and the improved estimators are obtained when p, the number of populations, is more than one.     

Moment method estimation of first-order continuous-time bilinear processes

In the present paper, we propose an estimation method of the first order continuous-time bilinear (COBL) process based on Euler-Maruyama discretization of the Itô solution asociated with the stochastic differerential equation (SDE) defining the process, and we suggest a standard moment method (MM) estimates of the unknown parameters involving in COBL process. So, some relationships linking the parameters and the theoretical moments of the process and its quadratic version are given. These relationships we allow to construct two algorithms to estimate the parameters based on MM. Using the fact that the incremented processes are strongly mixing with exponential rate whenever certain conditions are fulfilled, we show that the resulting estimators are strongly consistent and asymptotically normal. The theory can be applied to the COGARCH(1, 1), Gaussian Ornstein-Uhlenbeck (OU) models and among other specifications. Finite sample properties are also considered throught Monte-Carlo experimencts. In end, this algorithm is then used to model the exchanges rate of the Algerian Dinar against the US-dollar and against the single European currency.     

A genetic algorithm for thepart family formation problem

Recently, there has been a lot of interest in group technology (GT) from researchers as well as from practitioners. This interest is explained by the fact that GT supports new manufacturing philosophies. One of the main issues in GT is the part family formation problem which is concerned with grouping similar products into same families. Many researchers have tackled this problem and many algorithms have been proposed for it. In this paper, we present a genetic technique-based heuristic for the quadratic integer programming model of the part family formation problem which was formulated by Kusiak et al. (1986). The heuristic is tested on several problems from the literature, and preliminary results are very promising.     

Nonlinear voxel-based modelling of the haemodynamic response in fMRI

A common assumption for data analysis in functional magnetic resonance imaging is that the response signal can be modelled as the convolution of a haemodynamic response (HDR) kernel with a stimulus reference function. Early approaches modelled spatially constant HDR kernels, but more recently spatially varying models have been proposed. However, convolution limits the flexibility of these models and their ability to capture spatial variation. Here, a range of (nonlinear) parametric curves are fitted by least squares minimisation directly to individual voxel HDRs (i.e., without using convolution). A ‘constrained gamma curve’ is proposed as an efficient form for fitting the HDR at each individual voxel. This curve allows for spatial variation in the delay of the HDR, but places a global constraint on the temporal spread. The approach of directly fitting individual parameters of HDR shape is demonstrated to lead to an improved fit of response estimates.     

Smoothing parameter selection methods for nonparametric regression with spatially correlated errors

When spatial data are correlated, currently available data‐driven smoothing parameter selection methods for nonparametric regression will often fail to provide useful results. The authors propose a method that adjusts the generalized cross‐validation criterion for the effect of spatial correlation in the case of bivariate local polynomial regression. Their approach uses a pilot fit to the data and the estimation of a parametric covariance model. The method is easy to implement and leads to improved smoothing parameter selection, even when the covariance model is misspecified. The methodology is illustrated using water chemistry data collected in a survey of lakes in the Northeastern United States.