A class of distributions with the linear mean residual quantile function and it’s generalizations

In the present paper, we introduce and study a class of distributions that has the linear mean residual quantile function. Various distributional properties and reliability characteristics of the class are studied. Some characterizations of the class of distributions are presented. We then present generalizations of this class of distributions using the relationship between various quantile based reliability measures. The method of L-moments is employed to estimate parameters of the class of distributions. Finally, we apply the proposed class of distributions to a real data set.     

Nonparametric density deconvolution by weighted kernel estimators

Nonparametric density estimation in the presence of measurement error is considered. The usual kernel deconvolution estimator seeks to account for the contamination in the data by employing a modified kernel. In this paper a new approach based on a weighted kernel density estimator is proposed. Theoretical motivation is provided by the existence of a weight vector that perfectly counteracts the bias in density estimation without generating an excessive increase in variance. In practice a data driven method of weight selection is required. Our strategy is to minimize the discrepancy between a standard kernel estimate from the contaminated data on the one hand, and the convolution of the weighted deconvolution estimate with the measurement error density on the other hand. We consider a direct implementation of this approach, in which the weights are optimized subject to sum and non-negativity constraints, and a regularized version in which the objective function includes a ridge-type penalty. Numerical tests suggest that the weighted kernel estimation can lead to tangible improvements in performance over the usual kernel deconvolution estimator. Furthermore, weighted kernel estimates are free from the problem of negative estimation in the tails that can occur when using modified kernels. The weighted kernel approach generalizes to the case of multivariate deconvolution density estimation in a very straightforward manner.     

A new alternative to the standard F test for clustered data

The data collection process and the inherent population structure are the main causes for clustered data. The observations in a given cluster are correlated, and the magnitude of such correlation is often measured by the intra-cluster correlation coefficient. The intra-cluster correlation can lead to an inflated size of the standard F test in a linear model. In this paper, we propose a solution to this problem. Unlike previous adjustments, our method does not require estimation of the intra-class correlation, which is problematic especially when the number of clusters is small. Our simulation results show that the new method outperforms the existing methods.     

Analysis of robust design experiments with time-dependent ordinal response characteristics: a quality improvement study from the horticulture industry

An approach to the analysis of time-dependent ordinal quality score data from robust design experiments is developed and applied to an experiment from commercial horticultural research, using concepts of product robustness and longevity that are familiar to analysts in engineering research. A two-stage analysis is used to develop models describing the effects of a number of experimental treatments on the rate of post-sales product quality decline. The first stage uses a polynomial function on a transformed scale to approximate the quality decline for an individual experimental unit using derived coefficients and the second stage uses a joint mean and dispersion model to investigate the effects of the experimental treatments on these derived coefficients. The approach, developed specifically for an application in horticulture, is exemplified with data from a trial testing ornamental plants that are subjected to a range of treatments during production and home-life. The results of the analysis show how a number of control and noise factors affect the rate of post-production quality decline. Although the model is used to analyse quality data from a trial on ornamental plants, the approach developed is expected to be more generally applicable to a wide range of other complex production systems.     

A Weighted Least Squares Approach to Levene's Test of Homogeneity of Variance

In 1960 Levene suggested a potentially robust test of homogeneity of variance based on an ordinary least squares analysis of variance of the absolute values of mean-based residuals. Levene's test has since been shown to have inflated levels of significance when based on the F-distribution, and tests a hypothesis other than homogeneity of variance when treatments are unequally replicated, but the incorrect formulation is now standard output in several statistical packages. This paper develops a weighted least squares analysis of variance of the absolute values of both mean-based and median-based residuals. It shows how to adjust the residuals so that tests using the F -statistic focus on homogeneity of variance for both balanced and unbalanced designs. It shows how to modify the F -statistics currently produced by statistical packages so that the distribution of the resultant test statistic is closer to an F-distribution than is currently the case. The weighted least squares approach also produces component mean squares that are unbiased irrespective of which variable is used in Levene's test. To complete this aspect of the investigation the paper derives exact second-order moments of the component sums of squares used in the calculation of the mean-based test statistic. It shows that, for large samples, both ordinary and weighted least squares test statistics are equivalent; however they are over-dispersed compared to an F variable.     

CCD图像的轮廓特征点提取算法

采用最大方差法将图像二值化,用图像形态学的梯度﹑细化和修剪算法来提取边缘轮廓,利用十一点曲率法得到轮廓的角点和切点的大致位置。提出了一种基于最小二乘拟合的改进算法,来进一步确定角点和切点,并对轮廓分段识别。该算法应用在基于图像处理的刀具测量系统中,实际结果表明具有良好的抗噪声性能,能准确提取出图像的特征点。     

内在与超越——孔子中庸思想阐微

孔子思想中存在诸多二律背反式的冲突模式,比较突出的如天人冲突、礼仪冲突、德刑冲突、仕隐冲突。这些冲突关系中实含有相互依存、彼此互动的内涵。孔子通过“命”来调谐天与人的冲突,通过“诚”来达致礼与仪的统一,通过“仁”来实现德与刑的互补,通过“时”来决定仕与隐的抉择。孔子解决其思想中内心冲突的原则归根到底是他的中庸思想,“命”、“诚”、“仁”、“时”都只是中庸原则应用于不同类型的冲突模式所选取的具体超越路径。     

论老子美学的守中论和涤除论

老子守中论和涤除论的审美内涵和意义值得探讨。老子提出了其独特的语言观 ,倡导“大音希声”的本体论语言观。守中论的理性基础最终还是落实在了审美主体博大空灵、容纳无限的“涤除”胸襟。老子通过审美守中论、涤除论 ,揭示了审美活动的特殊性及必然性规律     

神的逻各斯翅膀——亚里士多德的理论对希腊正教的辩护

亚里士多德以其"中道观"、"辩正观"、"潜能与现实"关系以及"悲剧观"对希腊正教的辩护首先体现在希腊正教教堂风格的简朴和分布的密集;其次是恩典之道上的获恩与赐恩关系;再次是在原罪上的净化与自救原则.这些辩护充分反映了基督教在异邦传播中神学巧妙地借鉴和运用西方本土化的优势资源,特别是亚里士多德的伦理学、哲学和文学等的智慧资源而构成的成功范例,即为神学安插上了飞翔的逻各斯翅膀,为基督教在异邦传播提供了强有力的理论支持.     

论中国古代“中和”思维方式的发生

“中和”思维方式是中国古代哲学的基本思维方式之一 ,通过对“中和”思维方式发生的研究 ,不仅可以探索中国古代思维方式发生的一般规律 ,而且可以深化对中国传统文化的探讨。本文立足于中国古人的实践 ,运用辩证唯物主义的观点 ,探讨了“中和”思维方式发生的自然、社会条件 ,论述了“中和”思维方式在实践基础上生成的历史过程。