A new family of multivariate slash distributions

In this article, a new form of multivariate slash distribution is introduced and some statistical properties are derived. In order to illustrate the advantage of this distribution over the existing generalized multivariate slash distribution in the literature, it is applied to a real data set.     

Slashed generalized exponential distribution

In this paper, we introduce an extension of the generalized exponential (GE) distribution, making it more robust against possible influential observations. The new model is defined as the quotient between a GE random variable and a beta-distributed random variable with one unknown parameter. The resulting distribution is a distribution with greater kurtosis than the GE distribution. Probability properties of the distribution such as moments and asymmetry and kurtosis are studied. Likewise, statistical properties are investigated using the method of moments and the maximum likelihood approach. Two real data analyses are reported illustrating better performance of the new model over the GE model.     

A new heavy-tailed distribution defined on the bounded interval: the logit slash distribution and its application

This paper proposes a new heavy-tailed and alternative slash type distribution on a bounded interval via a relation of a slash random variable with respect to the standard logistic function to model the real data set with skewed and high kurtosis which includes the outlier observation. Some basic statistical properties of the newly defined distribution are studied. We derive the maximum likelihood, least-square, and weighted least-square estimations of its parameters. We assess the performance of the estimators of these estimation methods by the simulation study. Moreover, an application to real data demonstrates that the proposed distribution can provide a better fit than well-known bounded distributions in the literature when the skewed data set with high kurtosis contains the outlier observations.     

A new family of multivariate skew slash distribution

In this article, the new family of multivariate skew slash distribution is defined. According to the definition, a stochastic representation of the multivariate skew slash distribution is derived. The first four moments and measures of skewness and kurtosis of a random vector with the multivariate skew slash distribution are obtained. The distribution of quadratic forms for the multivariate skew slash distribution and the non central skew slash χ² distribution are studied. Maximum likelihood inference and real data illustration are discussed. In the end, the potential extension of multivariate skew slash distribution is discussed.     

山民下坝的文化适应——苦聪人定居问题研究

从 2 0世纪 50年代开始 ,政府就投入大量人力、物力、财力 ,动员中越边境地区迁徙游耕的苦聪人走出森林 ,下坝定居定耕 ,但苦聪人在定居与迁徙的选择中不断出现反复 ,历经 50年 ,到 2 0世纪末 ,苦聪人仍然没有全部定居下来。通过田野调查 ,笔者分析了苦聪人“屡定不居”的各种原因、定居后存在的问题及定居模式的选择等     

缙云山风灾迹地恢复群落植物种群生态位研究

以缙云山自然保护区风灾迹地恢复群落5个样地的调查资料为基础。采用生态位宽度、生态位相似比例和生态位重叠值公式,统计分析了风灾迹地恢复群落主要植物种群的生态位特征．研究结果表明：缙云山自然保护区风灾迹地恢复群落中乔木层四川山矾的生态位宽度最大,其次是四川大头茶和白毛新木姜子;灌木层和草本层生态位最宽的是菝葜和狗脊．生态位相似比例值在0．5以上的有74对,占总比例的61．67％,显示了优势种群之间的相似性比例值较大．风灾迹地恢复群落优势种群之间的生态位重叠程度较低,各种群对群落环境资源的分享比较充分,主要种群之间的关系较为协调和平衡,群落也处于相对稳定的状态．     

类型逻辑语法与汉语中的照应省略

现代汉语中存在大量语义资源重复使用的现象,最典型的是代词的回指照应、以及李艳惠在《省略与成分缺失》一文中提到的三种谓词省略结构[1]。在类型逻辑语法框架下,基于Jger构造的LLC系统添加针对"省略槽"引入范畴的规则eI,再借助照应算子的回指搜索功能,不但能够处理一般的代词回指、VP回指现象,还能够推广刻画汉语的多动词单句和兼语句等现象,获得正确的语义解读。可以证明,添加对应eI规则的公理的新系统在特定框架模型下是可靠并且完全的。     

缙云山风灾迹地恢复群落植物物种多样性

以缙云山自然保护区风灾迹地恢复群落5个样地调查资料为基础,研究了缙云山自然保护区风灾迹地恢复群落物种多样性的特征.结果表明：各样地间多样性指数测值变幅不大,物种多样性在群落不同层次的变化规律为：灌木层〉乔木层〉草本层.     

关于斜Laplace分布与Levy偏稳定分布的性质

目前有关重尾或偏态数据的统计分析和理论模型相对较少,基于传统的Laplace分布,提出一种处理偏态和重尾数据的新模型——斜Laplace分布,以研究其参数估计方法。利用数理统计知识推导出该分布与一些常见分布(如正态分布、指数分布)间的统计关系,并给出一种可通过设置不同参数值得到不同分布的Levy偏稳定分布及其稳定性。     

Generalized modified slash distribution with applications

Abstract

In this article a generalization of the modified slash distribution is introduced. This model is based on the quotient of two independent random variables, whose distributions are a normal and a one-parameter gamma, respectively. The resulting distribution is a new model whose kurtosis is greater than other slash distributions. The probability density function, its properties, moments, and kurtosis coefficient are obtained. Inference based on moment and maximum likelihood methods is carried out. The multivariate version is also introduced. Two real data sets are considered in which it is shown that the new model fits better to symmetric data with heavy tails than other slash extensions previously introduced in literature.