Collapsibility of Conditional Graphical Models

Abstract. In this paper, we consider two kinds of collapsibility, that is, the model‐collapsibility and the estimate‐collapsibility, of conditional graphical models for multidimensional contingency tables. We show that these two definitions are equivalent, and propose a sufficient and necessary condition for them in terms of the interaction graph, which allows the collapsibility to be characterized and judged intuitively and conveniently.     

A Likelihood-Based Approximation to the Cumulative Distribution Function of the Noncentral t Distribution

Optimal designs for estimating the parameters and also the optimum factor combinations in multiresponse experiments have been considered by various authors. However, till date, in mixture experiments optimum designs have been studied only in the single response case. In this article, attempt has been made to investigate optimum designs for estimating optimum mixing proportions in a multiresponse mixture experiment.     

Approximate Bayesian Computation for Exponential Random Graph Models for Large Social Networks

We consider the issue of sampling from the posterior distribution of exponential random graph (ERG) models and other statistical models with intractable normalizing constants. Existing methods based on exact sampling are either infeasible or require very long computing time. We study a class of approximate Markov chain Monte Carlo (MCMC) sampling schemes that deal with this issue. We also develop a new Metropolis–Hastings kernel to sample sparse large networks from ERG models. We illustrate the proposed methods on several examples.     

EGARCH Model with Weighted Liquidity

We analyze a variant of the EGARCH model which captures the variation of the intra-day price. We study the asymptotic behavior of the estimators for the parameters of the model. We also illustrate our theoretical results by empirical studies.     

Exponential Growth Model: From Horizontal to Linear Asymptote

We present a smooth function that can be used as regression curve for modeling growth phenomena requiring an increasing curvilinear concave asymptote. This model is obtained as the product of a concave asymptotic curve and the exponential model. In addition to its increasing character with a curvilinear asymptote, including horizontal or linear increasing asymptote, the resulting model provides curves with a single inflection point. Numerical examples are presented.     

On the simple step-stress model for two-parameter exponential distribution

In this paper, we consider the simple step-stress model for a two-parameter exponential distribution, when both the parameters are unknown and the data are Type-II censored. It is assumed that under two different stress levels, the scale parameter only changes but the location parameter remains unchanged. It is observed that the maximum likelihood estimators do not always exist. We obtain the maximum likelihood estimates of the unknown parameters whenever they exist. We provide the exact conditional distributions of the maximum likelihood estimators of the scale parameters. Since the construction of the exact confidence intervals is very difficult from the conditional distributions, we propose to use the observed Fisher Information matrix for this purpose. We have suggested to use the bootstrap method for constructing confidence intervals. Bayes estimates and associated credible intervals are obtained using the importance sampling technique. Extensive simulations are performed to compare the performances of the different confidence and credible intervals in terms of their coverage percentages and average lengths. The performances of the bootstrap confidence intervals are quite satisfactory even for small sample sizes.     

统计执法的博弈分析

针对目前中国统计数据失真相当严重并引起社会各界普遍关注的现象,运用博弈论作为分析工具,引入重复博弈研究了统计执法中数据报方与查方的利益冲突关系,从统计执法的角度揭示了统计数据失真的主要原因,并提出了相应的五项对策。     

经济增长由投资拉动转向消费拉动的现实选择——基于税收政策效应的实证分析

消费是影响和决定国民收入的重要因素,如何实现经济增长由投资拉动向消费拉动的转变,是当前经济形势下迫切需要解决的问题。通过引入虚拟变量,从税收政策视角建立消费函数计量模型,对影响中国居民消费行为的因素进行了量化和深入分析,并基于模型的分析结果给出了政策界面。     

基于时间序列分析方法的连续性抽样调查研究

针对连续性抽样调查中如何利用过去各期的调查信息来提高现期抽样估计精度的问题,引入时间序列分析方法,分别考虑连续性抽样调查中重复样本和重叠样本等不同情况,建立了不同情况下的时间序列模型,利用成熟的时间序列分析方法给出了总体特征的线性组合估计量。由于时间序列分析方法能够充分利用以往各期的调查信息,从而能够给出精度更高的估计量。     

中国收入分配不平等对经济增长影响的研究

文章利用中国30个省、直辖市、自治区1981-2005年的面板数据,运用面板数据模型分析中国收入分配不平等对经济增长的影响,结果表明中国短期内城乡收入差距有利于经济增长。