On ridge estimators for the negative binomial regression model

The negative binomial (NB) regression model is very popular in applied research when analyzing count data. The commonly used maximum likelihood (ML) estimator is very sensitive to highly intercorrelated explanatory variables. Therefore, a NB ridge regression estimator (NBRR) is proposed as a robust option of estimating the parameters of the NB model in the presence of multicollinearity. To investigate the performance of the NBRR and the traditional ML approach the mean squared error (MSE) is calculated using Monte Carlo simulations. The simulated result indicated that some of the proposed NBRR methods should always be preferred to the ML method.     

Conditional inference procedures for the Laplace distribution when the observed samples are progressively censored

In this paper, we develop procedures for obtaining confidence intervals for the parameters of a Laplace distribution as well as upper and lower γ probability tolerance intervals for a proportion β, given a progressively Type-II right censored sample from the Laplace distribution. The intervals are obtained by conditioning on the observed values of the ancillary statistics. The intervals are exact, do not require numerical integration, and generalize the work of Childs and Balakrishnan (1996) who considered the conventional Type-II right censored case. Received: February 2000     

Designs for Variance Components Estimation: Past and Present

This article provides (1) a comprehensive coverage of the literature on designs for estimating variance components, and (2) a review of recent applications of such designs in genetics, statistical process control, and quality improvement. In addition, recent methods of estimation of variance components and model forms, other than the linear, are discussed. The latter developments have a direct effect on the choice of design. Some suggested ideas for future research directions are also given.     

Three Sides of Smoothing: Categorical Data Smoothing, Nonparametric Regression, and Density Estimation

The past forty years have seen a great deal of research into the construction and properties of nonparametric estimates of smooth functions. This research has focused primarily on two sides of the smoothing problem: nonparametric regression and density estimation. Theoretical results for these two situations are similar, and multivariate density estimation was an early justification for the Nadaraya-Watson kernel regression estimator.
A third, less well-explored, strand of applications of smoothing is to the estimation of probabilities in categorical data. In this paper the position of categorical data smoothing as a bridge between nonparametric regression and density estimation is explored. Nonparametric regression provides a paradigm for the construction of effective categorical smoothing estimates, and use of an appropriate likelihood function yields cell probability estimates with many desirable properties. Such estimates can be used to construct regression estimates when one or more of the categorical variables are viewed as response variables. They also lead naturally to the construction of well-behaved density estimates using local or penalized likelihood estimation, which can then be used in a regression context. Several real data sets are used to illustrate these points.     

一种改进的中文分词算法

汉语自动分词是汉语信息处理的前提,词库是汉语自动分词的基础.文章提出了一种在对词库进行改造的基础上改进的匹配算法,突破了最大匹配分词算法分词的长度限制,提高了中文分词的速度和效率.     

提高DSRC道路信标定位精度的最大信号法及其工程实现

本文概述了中国外贸出口体制的改革进展和成就,探讨了WTO对出口体制的要求及中国出口体制与之相比存在的差距,并按照WTO原则和社会主义市场经济要求,对中国入世后进一步完善出口体制提出12个方面的主要措施。     

Periodic inspection plans: The case of Weibull distribution

In estimating the lifetime distribution of a product, the efficiency of a periodic inspection plan vis-á-vis with the continuous inspection plan is discussed. The periodic inspection plan envisages inspecting the units in the sample periodically at m successive equi-distant time points, for a given choice of m. The issue of choosing the value of m is also discussed. The discussions are carried out when the underlying lifetime distribution is Weibull.     

On the linear statistical relationship

The fitting of lines to data, when the relative precision of the measured data is a known constant, is a problem which is of some interest, for example in comparison of measurement procedures. We examine some ways of treating this problem with a view to clarifying the relationship of solutions with the Maximum Likelihood Estimate. Acknowledgement. I am grateful to Hans Schneeweiss for suggesting a strengthened form of the definition of f in Section 4.     

基于VCR模型的空间相关信道下V-BLAST系统性能分析

本文研究了空间相关信道下V-BLAST系统的最大似然检测性能.本文的分析基于VCR信道模型,它可以描述本地相关和非本地相关同时存在的情形.通过推导成对错误概率的精确表达式,得出系统误比特率的联合界,并利用成对错误概率在高信噪比下的近似表达式,研究了系统的分集性能,最后用计算机仿真对理论分析进行了验证.     

Properties of h-Likelihood Estimators in Clustered Data

We study properties of the maximum h-likelihood estimators for random effects in clustered data. To define optimality in random effects predictions, several foundational concepts of statistics such as likelihood, unbiasedness, consistency, confidence distribution and the Cramer–Rao lower bound are extended. Exact probability statements about interval estimators for random effects can be made asymptotically without a prior assumption. Using the binary-matched pair example, we illustrated that the use of random effects recover information, leading to the boon on estimating treatment effects.