Estimation of signal to noise ratio using mahalanobis distance

In this paper, we propose some alternative estimatiors to that given by C. G. Khatri and C. R. Rao (1985), for estimating Signal to Noise ratio. Using Pitman Nearness, Condition for prefering one estimator over the other is estabilished. It is shown numerically that estimators corresponding to Entropy loss function are better more oftern than those corresponding to Squared Error loss.     

Interval censored and truncated data: Rate of convergence of NPMLE of the density

We consider survival data that are both interval censored and truncated. Under appropriate assumptions on the involved distributions, the censoring, truncation and survival, we prove the consistency of the NPMLE of the density of the survival, and give the rate of convergence. Finally, we give an example where the joint law of the censoring and truncation can be explicitly computed.     

校园网与现代教育

探讨了校园网和现代教育的关系 ,校园网络可以成为现代教育的平台和核心 ,围绕着校园网建设面向未来的现代教育 ,着重阐述了校园网络建设应该注意的问题。     

师生人际距离新论

人际距离是影响人际关系的一个重要因素,贯穿于整个教育过程中的师生距离是人际关系的重要内容,是影响师生交往,进而影响教育教学效果的一个关键因素.师生距离到底该近还是该远,一直是教育理论界热衷的话题.本文结合多年实践中的教育实例,就师生距离的远近问题作一新探讨与解读.     

我国高水平女子中长跑运动员训练疲劳效应特征研究

从适应—疲劳学说视角对女子中长跑训练疲劳效应进行研究分析,认为运动训练本身会产生负效应现象.我国奥运会优势项目女子中长跑运动员在黄金年龄因伤被迫退役就是教练在训练中忽视运动训练负效应人为地造成的,这也提示我国教练:运动训练本身具有负效应,在中长跑训练中要重视和借鉴国外教练的"两极化"训练模式,增加有氧训练的比例.     

关于n维单形宽度的一个结果

证明了关于ｎ维单形宽度的一个不等式，结果是Ｗ≤（ｓｉｎθ）１／２αｎ１ｎ＋１ｎ＋１ｉ＝１Ｒ２ｉ１／２．这一结果蕴含并推广了Ｓａｌｅｅ－Ａｌｅｘａｎｄｅｒ定理     

Estimation for u-shaped beta distributions: minimum hellinger distance and related methods

We compare minimum Hellinger distance and minimum Heiiinger disparity estimates for U-shaped beta distributions. Given suitable density estimates, both methods are known to be asymptotically efficient when the data come from the assumed model family, and robust to small perturbations from the model family. Most implementations use kernel density estimates, which may not be appropriate for U-shaped distributions. We compare fixed binwidth histograms, percentile mesh histograms, and averaged shifted histograms. Minimum disparity estimates are less sensitive to the choice of density estimate than are minimum distance estimates, and the percentile mesh histogram gives the best results for both minimum distance and minimum disparity estimates. Minimum distance estimates are biased and a bias-corrected method is proposed. Minimum disparity estimates and bias-corrected minimum distance estimates are comparable to maximum likelihood estimates when the model holds, and give better results than either method of moments or maximum likelihood when the data are discretized or contaminated, Although our re¬sults are for the beta density, the implementations are easily modified for other U-shaped distributions such as the Dirkhlet or normal generated distribution.     

Bayesian estimation and influence diagnostics of generalized partially linear mixed-effects models for longitudinal data

This paper develops a Bayesian approach to obtain the joint estimates of unknown parameters, nonparametric functions and random effects in generalized partially linear mixed models (GPLMMs), and presents three case deletion influence measures to identify influential observations based on the φ-divergence, Cook's posterior mean distance and Cook's posterior mode distance of parameters. Fisher's iterative scoring algorithm is developed to evaluate the posterior modes of parameters in GPLMMs. The first-order approximation to Cook's posterior mode distance is presented. The computationally feasible formulae for the φ-divergence diagnostic and Cook's posterior mean distance are given. Several simulation studies and an example are presented to illustrate our proposed methodologies.     

Detection of outliers in simple circular regression models using the mean circular error statistic

The investigation on the identification of outliers in linear regression models can be extended to those for circular regression case. In this paper, we propose a new numerical statistic called mean circular error to identify possible outliers in circular regression models by using a row deletion approach. Through intensive simulation studies, the cut-off points of the statistic are obtained and its power of performance investigated. It is found that the performance improves as the concentration parameter of circular residuals becomes larger or the sample size becomes smaller. As an illustration, the statistic is applied to a wind direction data set.     

基于有效预测区域的模糊数据关联

多目标多传感器跟踪系统由数据关联和目标状态估计两部分组成,数据关联是多目标跟踪系统研究的核心。数据关联和目标状态估计两部分既有一定的独立性又有密切的联系,而将两部分合理地结合对提高跟踪系统的性能是重要的。该文以跟踪目标的有效预测区域为依据,利用基于Mahalanobis距离的模糊均值聚类方法解决数据关联问题,在一定程度上将数据关联和目标状态估计两个不同的过程相结合,仿真计算说明了其有效性。