Estimation of noncentrality parameters

We propose some estimators of noncentrality parameters which improve upon usual unbiased estimators under quadratic loss. The distributions we consider are the noncentral chi-square and the noncentral F. However, we give more general results for the family of elliptically contoured distributions and propose a robust dominating estimator.     

分析Chiral分层媒质特性的一般方法(英文)

提出了一套系统方法用于求解任意导体片位于界面的Chiral分层媒质的谐振频率,衰减因子和电磁场分布。文中的分析是在Fourier变换域的并矢格林函数和矩阵分析的基础上来进行的,给出的公式的最大价值在于它提供了求解Chiral分层媒质问题的方法论。     

线性矩阵不等式问题的进化计算解决方法

针对决定模糊控制中稳定性的线性矩阵不等式问题,提出了用进化计算来解决模糊控制中线性矩阵不等式的新算法。实验证明,该算法解“用于实现模糊控制的增益调度和稳定性的线性矩阵不等式”是有效的。     

基于FCM的动态结合全局图像阈值分割

全局阈值分割对于小目标物效果不理想,动态阈值容易产生阴影等干扰,但综合考虑全局阈值和动态阈值可以达到比较理想的结果。模糊C均值算法用于灰度图像分割是一种非监督模糊聚类后再标定的过程,该文在不明显增加运算量的前提下,利用模糊C均值自动聚类的功能分别得到全局阈值和动态阈值,完成对阈值矩阵的构造和图像的分割。     

Generalized additive models for location, scale and shape

Summary.  A general class of statistical models for a univariate response variable is presented which we call the generalized additive model for location, scale and shape (GAMLSS). The model assumes independent observations of the response variable y given the parameters, the explanatory variables and the values of the random effects. The distribution for the response variable in the GAMLSS can be selected from a very general family of distributions including highly skew or kurtotic continuous and discrete distributions. The systematic part of the model is expanded to allow modelling not only of the mean (or location) but also of the other parameters of the distribution of y , as parametric and/or additive nonparametric (smooth) functions of explanatory variables and/or random-effects terms. Maximum (penalized) likelihood estimation is used to fit the (non)parametric models. A Newton–Raphson or Fisher scoring algorithm is used to maximize the (penalized) likelihood. The additive terms in the model are fitted by using a backfitting algorithm. Censored data are easily incorporated into the framework. Five data sets from different fields of application are analysed to emphasize the generality of the GAMLSS class of models.     

Bayesian analysis of a marked point process: Application in seismic hazard assessment

Point processes are the stochastic models most suitable for describing physical phenomena that appear at irregularly spaced times, such as the earthquakes. These processes are uniquely characterized by their conditional intensity, that is, by the probability that an event will occur in the infinitesimal interval (t, t+Δt), given the history of the process up tot. The seismic phenomenon displays different behaviours on different time and size scales; in particular, the occurrence of destructive shocks over some centuries in a seismogenic region may be explained by the elastic rebound theory. This theory has inspired the so-called stress release models: their conditional intensity translates the idea that an earthquake produces a sudden decrease in the amount of strain accumulated gradually over time along a fault, and the subsequent event occurs when the stress exceeds the strength of the medium. This study has a double objective: the formulation of these models in the Bayesian framework, and the assignment to each event of a mark, that is its magnitude, modelled through a distribution that depends at timet on the stress level accumulated up to that instant. The resulting parameter space is constrained and dependent on the data, complicating Bayesian computation and analysis. We have resorted to Monte Carlo methods to solve these problems.     

Real nonparametric regression using complex wavelets

Summary.  Wavelet shrinkage is an effective nonparametric regression technique, especially when the underlying curve has irregular features such as spikes or discontinuities. The basic idea is simple: take the discrete wavelet transform of data consisting of a signal corrupted by noise; shrink or remove the wavelet coefficients to remove the noise; then invert the discrete wavelet transform to form an estimate of the true underlying curve. Various researchers have proposed increasingly sophisticated methods of doing this by using real-valued wavelets. Complex-valued wavelets exist but are rarely used. We propose two new complex-valued wavelet shrinkage techniques: one based on multiwavelet style shrinkage and the other using Bayesian methods. Extensive simulations show that our methods almost always give significantly more accurate estimates than methods based on real-valued wavelets. Further, our multiwavelet style shrinkage method is both simpler and dramatically faster than its competitors. To understand the excellent performance of this method we present a new risk bound on its hard thresholded coefficients.     

国有企业的特殊性与我国国有企业的布局定位

国有企业特殊性的真实内涵表现为,它有着特殊的所有者和所有者代表、特殊的社会目标、特殊的社会经济功能和特殊的产权组织运作机制。因此,越是在以社会目标为主的产业领域,国有企业就越有存在的价值。尽管国有企业的布局是一种趋向性和开放式的动态布局,但它所传递的信息表明国有企业会在特殊产业领域中以合适的方式继续存在并扮演重要角色。     

Testing symmetry under a skew Laplace model

We develop tests of hypothesis about symmetry based on samples from possibly asymmetric Laplace distributions and present exact and limiting distribution of the test statistics. We postulate that the test statistic derived under the Laplace model is a rational choice as a measure of skewness and can be used in testing symmetry for other, quite general classes of skew distributions. Our results are applied to foreign exchange rates for 15 currencies.     

主动适应教师教育需要努力提高办学水平——对吉林师范大学发展定位与学科建设若干问题的个案思考

本文从分析吉林师范大学的发展定位与学科建设等具体问题入手,对有关教师教育和普通高师院校发展趋势、前景等一系列重要理论与实践问题进行了探讨.尽快提高办学水平是适应教师教育的迫切需要,准确定位是确定学校发展战略的前提,学科建设是提高办学水平的中心环节,调整优化学科专业结构是学科建设的主要途径.