A robust approach to longitudinal data analysis

The author introduces robust techniques for estimation, inference and variable selection in the analysis of longitudinal data. She first addresses the problem of the robust estimation of the regression and nuisance parameters, for which she derives the asymptotic distribution. She uses weighted estimating equations to build robust quasi‐likelihood functions. These functions are then used to construct a class of test statistics for variable selection. She derives the limiting distribution of these tests and shows its robustness properties in terms of stability of the asymptotic level and power under contamination. An application to a real data set allows her to illustrate the benefits of a robust analysis.     

Graphical models for skew-normal variates

This paper explores the usefulness of the multivariate skew-normal distribution in the context of graphical models. A slight extension of the family recently discussed by Azzalini & Dalla Valle (1996 ) and Azzalini & Capitanio (1999 ) is described, the main motivation being the additional property of closure under conditioning. After considerations of the main probabilistic features, the focus of the paper is on the construction of conditional independence graphs for skew-normal variables. Necessary and sufficient conditions for conditional independence are stated, and the admissible structures of a graph under restriction on univariate marginal distribution are studied. Finally, parameter estimation is considered. It is shown how the factorization of the likelihood function according to a graph can be rearranged in order to obtain a parameter based factorization.     

Saddlepoint approximations for some models of circular data

In this article we provide saddlepoint approximations for some important models of circular data. The particularity of these saddlepoint approximations is that they do not require solving the saddlepoint equation iteratively, so their evaluation is immediate. We first give very accurate approximations to P-values, critical values and power functions for some optimal tests regarding the concentration parameter under wrapped symmetric α-stable and circular normal models. Then, we consider an approximation to the distribution of a projection of the two-dimensional Pearson random walk with exponential step sizes.     

基于振动分析的工程结构损伤识别技术综述

综述了基于振动分析的工程结构损伤识别方法,并对各种方法进行了评述。根据国内外文献,对基于振动分析的工程结构损伤识别技术的发展趋势进行了展望。     

铝合金材料LY12CZ临界空穴扩张比的适用性探讨

对光滑试样和 3种不同曲率半径的切口试样 ,采用拉伸试验和电镜观测相结合的方法 ,研究了铝合金材料LY12CZ的VGC 参数的适用性。证实VGC 参数对材料的断裂形式较为敏感 ,适用于以拉伸型断裂为主的切口试样 ,对以剪切断裂为主的光滑拉伸试样不适用。     

SINUMERIK数控系统在车床改造中的应用

SINUMERIK80 2S数控系统用于C0 630车床电控系统改造。本文介绍CNC系统结构、电控系统改造方案及数控系统内部参数整定方法。     

伽马分布的形状参数的一种估计

本文利用服从伽马分布的随机变量 X 与其逆 X~(-1)的协方差只与形状参数有关这一性质,给出伽马分布形状参数的所谓自逆协方差估计,进而构造了相应的无偏估计,并证明了这类估计的大样本性质:强相合性以及渐近正态性。     

INFERENCE ABOUT THE MEAN OF A POISSON DISTRIBUTION IN THE PRESENCE OF A NUISANCE PARAMETER

In this note we examine the problem of estimating the mean of a Poisson distribution when a nuisance parameter is present. Using a condition of Cox (1958) about ancillarity in the presence of a nuisance parameter, we justify that inference about the parameter should be carried out using the conditional distribution given the appropriate ancillary statistics. A small simulation study has been done to compare the performance of the conditional likelihood approach and the standard likelihood approach.     

MOSFET中1/f噪声的Hooge参数α_H

本文报道 P 沟道 MOSFET 器件中 1/f 噪声 Hooge 参数测量的部分实验结果.由加利福尼亚州的 SILICONIX 公司提供的实验样品是采用同样工艺作在同一块基片之上的.实验表明,在由非谐和状态到谐和状态过渡时,α_H 与沟道长度的平方成正比.类似的结果未曾见报道.     

Estimation of parameters in survey sampling: Optimality

Some recent works on estimation in survey sampling are analyzed and extended from the perspective of the theory of optimal estimating functions.