Averaging Lorenz curves

A large number of functional forms has been suggested in the literature for estimating Lorenz curves that describe the relationship between income and population shares. The traditional way of overcoming functional-form uncertainty when estimating a Lorenz curve is to choose the function that best fits the data in some sense. In this paper we describe an alternative approach for accommodating functional-form uncertainty, namely, how to use Bayesian model averaging to average the alternative functional forms. In this averaging process, the different Lorenz curves are weighted by their posterior probabilities of being correct. Unlike a strategy of picking the best-fitting function, Bayesian model averaging gives posterior standard deviations that reflect the functional-form uncertainty. Building on our earlier work (Chotikapanich and Griffiths, 2002), we construct likelihood functions using the Dirichlet distribution and estimate a number of Lorenz functions for Australian income units. Prior information is formulated in terms of the Gini coefficient and the income shares of the poorest 10% and poorest 90% of the population. Posterior density functions for these quantities are derived for each Lorenz function and are averaged over all the Lorenz functions.     

Generalized additive models for location, scale and shape

Summary.  A general class of statistical models for a univariate response variable is presented which we call the generalized additive model for location, scale and shape (GAMLSS). The model assumes independent observations of the response variable y given the parameters, the explanatory variables and the values of the random effects. The distribution for the response variable in the GAMLSS can be selected from a very general family of distributions including highly skew or kurtotic continuous and discrete distributions. The systematic part of the model is expanded to allow modelling not only of the mean (or location) but also of the other parameters of the distribution of y , as parametric and/or additive nonparametric (smooth) functions of explanatory variables and/or random-effects terms. Maximum (penalized) likelihood estimation is used to fit the (non)parametric models. A Newton–Raphson or Fisher scoring algorithm is used to maximize the (penalized) likelihood. The additive terms in the model are fitted by using a backfitting algorithm. Censored data are easily incorporated into the framework. Five data sets from different fields of application are analysed to emphasize the generality of the GAMLSS class of models.     

Bayesian analysis of a marked point process: Application in seismic hazard assessment

Point processes are the stochastic models most suitable for describing physical phenomena that appear at irregularly spaced times, such as the earthquakes. These processes are uniquely characterized by their conditional intensity, that is, by the probability that an event will occur in the infinitesimal interval (t, t+Δt), given the history of the process up tot. The seismic phenomenon displays different behaviours on different time and size scales; in particular, the occurrence of destructive shocks over some centuries in a seismogenic region may be explained by the elastic rebound theory. This theory has inspired the so-called stress release models: their conditional intensity translates the idea that an earthquake produces a sudden decrease in the amount of strain accumulated gradually over time along a fault, and the subsequent event occurs when the stress exceeds the strength of the medium. This study has a double objective: the formulation of these models in the Bayesian framework, and the assignment to each event of a mark, that is its magnitude, modelled through a distribution that depends at timet on the stress level accumulated up to that instant. The resulting parameter space is constrained and dependent on the data, complicating Bayesian computation and analysis. We have resorted to Monte Carlo methods to solve these problems.     

Real nonparametric regression using complex wavelets

Summary.  Wavelet shrinkage is an effective nonparametric regression technique, especially when the underlying curve has irregular features such as spikes or discontinuities. The basic idea is simple: take the discrete wavelet transform of data consisting of a signal corrupted by noise; shrink or remove the wavelet coefficients to remove the noise; then invert the discrete wavelet transform to form an estimate of the true underlying curve. Various researchers have proposed increasingly sophisticated methods of doing this by using real-valued wavelets. Complex-valued wavelets exist but are rarely used. We propose two new complex-valued wavelet shrinkage techniques: one based on multiwavelet style shrinkage and the other using Bayesian methods. Extensive simulations show that our methods almost always give significantly more accurate estimates than methods based on real-valued wavelets. Further, our multiwavelet style shrinkage method is both simpler and dramatically faster than its competitors. To understand the excellent performance of this method we present a new risk bound on its hard thresholded coefficients.     

国有企业的特殊性与我国国有企业的布局定位

国有企业特殊性的真实内涵表现为,它有着特殊的所有者和所有者代表、特殊的社会目标、特殊的社会经济功能和特殊的产权组织运作机制。因此,越是在以社会目标为主的产业领域,国有企业就越有存在的价值。尽管国有企业的布局是一种趋向性和开放式的动态布局,但它所传递的信息表明国有企业会在特殊产业领域中以合适的方式继续存在并扮演重要角色。     

Testing symmetry under a skew Laplace model

We develop tests of hypothesis about symmetry based on samples from possibly asymmetric Laplace distributions and present exact and limiting distribution of the test statistics. We postulate that the test statistic derived under the Laplace model is a rational choice as a measure of skewness and can be used in testing symmetry for other, quite general classes of skew distributions. Our results are applied to foreign exchange rates for 15 currencies.     

密度分布非均匀的反馈控制Logistic单种群模型平衡态的稳定性

本文对种群密度在非均匀分布情形下,考虑了具反馈控制的滞后 Logistic 生态模型平衡位置的稳定性;分别给出了在常时滞和弱连续时滞以及强连续时滞情况下的稳定性条件;其结果是对 Gopalsamy 在密度均匀分布情形下相应结果的推广.     

多源模型的新进展

本文总结了高能核—核碰撞的多源模型自1987年提出到1990年以来的主要进展,着重介绍多源模型的基本物理思想及其在两种不同方案下的发展动态.通过与最新实验数据比较,说明多源模型能够成功地解释高能重离子碰撞的整体性质.     

论按劳分配与按生产要素分配的有机结合

在社会主义市场经济条件下坚持按劳分配的主体地位,既是社会主义生产过程本身的客观要求,也是社会主义市场经济健康发展的现实要求。同时,由于多种所有制及多元产权主体的存在,作为市场机制在分配领域发挥作用的具体表现,按生产要素分配在社会主义市场经济条件下也具有必然性。实践中,必须在全面认识二者对立统一关系的基础上,从微观经济领域的运行层次和所有制结构层次以及宏现经济运行层次实现按劳分配与按生产要素分配的有机结合。     

试析我国收入分配中的公平问题

收入分配公平是一个历史性范畴,它的内涵随生产关系的变化而变化.正确理解我国收入分配的公平,必须搞清楚机会公平与结果公平、收入分配公平与社会主义市场经济的关系,确立初次分配注重效率,再分配注重结果公平的分配范式.在分配中,防止平均主义,保持合理差距,反对两极分化,坚持效率优先、兼顾公平的原则,促进我国生产力的发展,不断提高人民群众的生活水平.