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.     

Bayesian autoregressive spectral analysis

The article describes an operational Bayesian approach to making inferences for the spectral density function for univariate autoregressive processes and for the AR operator of multivariate autoregressive processes. The derivation of the approach is described. Numerical examples, including the Wolfer Sunspot numbers, are used to demonstrate the practical usefulness of the approach.     

Dot Plots

Dot plots represent individual observations in a batch of data with symbols, usually circular dots. They have been used for more than 100 years to depict distributions in detail. Hand-drawn examples show their authors' efforts to arrange symbols so that they are as near as possible to their proper locations on a scale without overlapping enough to obscure each other. Recent computer programs that attempt to reproduce these historical plots have unfortunately resorted to simple histogram binning instead of using methods that follow the rules for the hand-drawn examples. This article introduces an algorithm that more accurately represents the dot plots cited in the literature.     

Unbiastld estimation of parametric functions in sampling from two two-truncation parameter families

We consider the problem of UMVU estimation of a U-estimable function of four unknown truncation parameters based on two independent random samples from two two-truncation parameter families. In particular, we obtain the UMVU estimator of functional, P (Y > X). Also the confidence intervals for some parametric functions are obtained.     

Nonparametric regression with cross‐classified responses

In this article, we develop regression models with cross‐classified responses. Conditional independence structures can be explored/exploited through the selective inclusion/exclusion of terms in a certain functional ANOVA decomposition, and the estimation is done nonparametrically via the penalized likelihood method. A cohort of computational and data analytical tools are presented, which include cross‐validation for smoothing parameter selection, Kullback–Leibler projection for model selection, and Bayesian confidence intervals for odds ratios. Random effects are introduced to model possible correlations such as those found in longitudinal and clustered data. Empirical performances of the methods are explored in simulation studies of limited scales, and a real data example is presented using some eyetracking data from linguistic studies. The techniques are implemented in a suite of R functions, whose usage is briefly described in the appendix. The Canadian Journal of Statistics 39: 591–609; 2011. © 2011 Statistical Society of Canada     

Wavelet density estimation for negatively associated stratified size-biased sample

This paper provides upper bounds of wavelet estimations on L^p (1≤p<∞) risk for a density function in Besov spaces based on negatively associated stratified size-biased random samples. It turns out that the classical theorem of Donoho, Johnstone, Kerkyacharian and Picard is completely extended to more general cases. More precisely, we consider the model with multiplication noise and allow the sample negatively associated. Our theory is illustrated with a simulation study.     

Limited information bayesian analysis of a structural coefficient in a simultaneous equations system

An analytical expression is obtained for the marginal posterior density for a structural coefficient in a simultaneous equations system based on a limited information Bayesian analysis. A con- ditional posterior density is obtained given reduced form para- meters. This conditional posterior density is in univariate student t form. Numerical examples suggest that the conditional density hasa tighter distribution around the posterior mean than the unconditional density when the correlation between the endo- genous variables and the structural error term is high.     

Urban forest cover of the Chicago region and its relation to household density and income

Urban forests and herbaceous open space play a vital role in the environmental and aesthetic health of cities, yet they are rarely identified in land-use inventories of urban areas. To provide information on urban forests and other vegetative land cover in Illinois cities, Landsat Thematic Mapper (TM) data from June 27, 1988, were classified for the Chicago metropolitan region (9,717 km²). Ten land-cover classes were identified, including two types of forestland (occupying 5.8% of the total area), residential land with trees (14.6%) or without trees (7.8%), cropland (37.5%), two types of grassland (7.7%), urban with impervious surfaces (23.1%), water (1.6%), and miscellaneous vegetation (2.1%). Correlation analyses indicated that household income and household density are strongly related to land covers in the region, particularly those with tree cover and urbanized land. Population changes for 1980–1985 and 1985–2010 (projected) show a pattern of increasing density in the urbanized zone concurrent with continued urban sprawl, primarily into current cropland.     

Coverage plots for assessing the variability of estimated contours of a density

Methods for assessing the variability of an estimated contour of a density are discussed. A new method called the coverage plot is proposed. Techniques including sectioning and bootstrap techniques are compared for a particular problem which arises in Monte Carlo simulation approaches to estimating the spatial distribution of risk in the operation of weapons firing ranges. It is found that, for computational reasons, the sectioning procedure outperforms the bootstrap for this problem. The roles of bias and sample size are also seen in the examples shown.     

元话语与大学英语中的写作教学

元话语 (metadiscourse)是指语篇中能标示话语结构、提请对方注意或表明发话者态度的各种语言手段。本文首先对元话语的概念、功能、分类进行了解释 ,然后探讨了元话语的使用情况与写作的关系 ,认为关键是看元话语在语篇中的使用是否“适当”和“有效” ,在写作方面起重要作用的是元话语的质量而不是数量 ,最后介绍了部分以提高写作质量为目的而进行的关于元话语的教学尝试