SB-Robust Estimators of the Parameters of the Wrapped Normal Distribution

In this article, we study the SB-robustness of various estimators of the mean direction (μ) and the concentration parameter (ρ) of the wrapped normal distribution. The functional corresponding to the sample mean direction is seen to be not SB-robust as an estimator of μ at the family of wrapped normal distributions with varying ρ, whereas the γ-trimmed mean direction is SB-robust at the same family of distributions for the different dispersion measures considered in this article. We also study the SB-robustness of the moment estimator of ρ and also that for a newly introduced trimmed estimator of ρ.     

On optimality of the horvitz-thompson estimator under a markov process model

For any varying probability sampling design the Horvitz-Thompson (1952) estimator is shown to be optimal within the class of all unbiased estimators of a finite population total under a Markov process model     

A measure and a graphical method for evaluating slope rotatability in response surface designs

A measure for evaluating slope rotatability over all directions in response surface designs, is proposed. This measure is used to form slope variance dispersion graph evaluating the overall slope rotatability and the slope estimation capability of an experimental design throughout the region of interest. This graph allows for an easy comparison of competing designs.     

A practical extension of the generalized estimating equation approach for longitudinal data

Liang and Zeger (1986) proposed an extension of generalized linear models to the analysis of longitudinal data. In their formulation, a common dispersion parameter assumption across observation times is required. However, this assumption is not expected to hold in most situations. Park (1993) proposed a simple extension of Liang and Zeger's formulation to allow for different dispersion parameters for each time point. The proposed model is easy to apply without heavy computations and useful to handle the cases when variations in over-dispersion over time exist. In this paper, we focus on evaluating the effect of additional dispersion parameters on the estimators of model parameters. Through a Monte Carlo simulation study, efficiency of Park's method is compared with the Liang and Zeger's method.     

复杂渐变线的分析与综合

给出了一种渐变线分析和综合的数值方法，该方法考虑了传播常数沿渐变线变化的因素以及色散效应，能对ＴＥＭ波和非ＴＥＭ波传输线的渐变结构作较好的近似处理，得到分析和综合复杂渐变线的普遍表达式。通过计算机优化方法，可直接得到渐变线的设计尺寸。在优化设计中，通过取不同的目标函数，能实现任意频率响应的渐变线。     

双光栅压缩器对线性频率啁光脉冲的压缩特性

本文提出了光栅时间色散的概念,给出了分析双光栅压缩器产生二次相位修正的一种简洁、新颖的方法,并由此讨论了双光栅压缩器对线性频率啁啾光脉冲的压缩特性.     

The robustness of point optimal testing for rosenberg random regression coefficients

The literature on testing for the presence of Rosenberg's (1973) return to normalcy random coefficient model is well developed with both Shively (1988) and Brooks (1993) advocating the use of point optimal tests. This paper explores the robustness of point optimal testing for the Rosenberg alternative to two departures: the special case HildrethHouck (1968) alternative and non-normality in regression disturbances, finding the point optimal testing approach to be fairly robust to both departures.     

双重广义线性模型在车损险费率厘定中的应用

双重广义线模型是对广义线性模型的扩展,其对反应变量的均值与散度参数同时建立模型,提高了模型运用的灵活性与适应性。将双重广义线性模型应用到车损险费率厘定中,既考虑了费率期望值与费率因子之间的关系,又考虑了变量的分散程度与费率因子之间的关系,并以欧洲一家保险公司的汽车保险损失数据为样本进行实证研究,把无索赔优待等级、地区、车型与年均行驶里程数作为费率因子,建立了费率厘定模型。结果表明,所得到费率结构合理,符合实际。     

A Bayesian approach to analyse overdispersed longitudinal count data

In this paper, we consider a model for repeated count data, with within-subject correlation and/or overdispersion. It extends both the generalized linear mixed model and the negative-binomial model. This model, proposed in a likelihood context [17 G. Molenberghs, G. Verbeke, and C.G.B. Demétrio, An extended random-effects approach to modeling repeated, overdispersion count data, Lifetime Data Anal. 13 (2007), pp. 457–511.[Web of Science ®] , [Google Scholar],18 G. Molenberghs, G. Verbeke, C.G.B. Demétrio, and A. Vieira, A family of generalized linear models for repeated measures with normal and conjugate random effects, Statist. Sci. 25 (2010), pp. 325–347. doi: 10.1214/10-STS328[Crossref], [Web of Science ®] , [Google Scholar]] is placed in a Bayesian inferential framework. An important contribution takes the form of Bayesian model assessment based on pivotal quantities, rather than the often less adequate DIC. By means of a real biological data set, we also discuss some Bayesian model selection aspects, using a pivotal quantity proposed by Johnson [12 V.E. Johnson, Bayesian model assessment using pivotal quantities, Bayesian Anal. 2 (2007), pp. 719–734. doi: 10.1214/07-BA229[Crossref], [Web of Science ®] , [Google Scholar]].     

Layered clays in PP polymer dispersion: the effect of the processing conditions

The effect of processing conditions of material and interfacial/ interphase properties in clay/polymer nanocomposites are usually studied through experimental results of X-ray diffraction, transmission electron microscopy and rheology mechanical tests. In this paper, the interaction of the experimental parameters and properties measure results are studied by employing multivariate analysis of variance technique. This model is used to establish relations between several material and interfacial/interphase characteristics with the processing conditions. These results are then analyzed in detail, using univariate approach (analysis of variance), to point out the existing significant relations. In general, agreement with experimental observations was found, but few other nonagreeable things are found out, which must be studied in the future. The effects of all parameters are thus determined, using these new approach, to predict the relations between material and interfacial/interphase properties, without the need to duplicate experiments in laboratory.