Detecting Variance Change-Points for Blocked Time Series and Dependent Panel Data

This article proposes a class of weighted differences of averages (WDA) statistics to test and estimate possible change-points in variance for time series with weakly dependent blocks and dependent panel data without specific distributional assumptions. We derive the asymptotic distributions of the test statistics for testing the existence of a single variance change-point under the null and local alternatives. We also study the consistency of the change-point estimator. Within the proposed class of the WDA test statistics, a standardized WDA test is shown to have the best consistency rate and is recommended for practical use. An iterative binary searching procedure is suggested for estimating the locations of possible multiple change-points in variance, whose consistency is also established. Simulation studies are conducted to compare detection power and number of wrong rejections of the proposed procedure to that of a cumulative sum (CUSUM) based test and a likelihood ratio-based test. Finally, we apply the proposed method to a stock index dataset and an unemployment rate dataset. Supplementary materials for this article are available online.     

The Distribution of the Kolmogorov–Smirnov,Cramer–von Mises,and Anderson–Darling Test Statistics for Exponential Populations with Estimated Parameters

This article presents a derivation of the distribution of the Kolmogorov–Smirnov, Cramer–von Mises, and Anderson–Darling test statistics in the case of exponential sampling when the parameters are unknown and estimated from sample data for small sample sizes via maximum likelihood.     

Modified goodness-of-fit test for the laplace distribution

In this paper critical values of the Anderson-Darling and Cra[macute]er-von Mises are given for the Laplace distribution for maximum likelihood estimation of the location and scale parameters. The power of these tests is investigated for a number of alternative distributions. The Anderson-Darling test yields higher power generally than the Cra[macute]er-von Mises test.     

Likelihood inference for correlated binary data without any information about the joint distributions

We propose a universal robust likelihood that is able to accommodate correlated binary data without any information about the underlying joint distributions. This likelihood function is asymptotically valid for the regression parameter for any underlying correlation configurations, including varying under- or over-dispersion situations, which undermines one of the regularity conditions ensuring the validity of crucial large sample theories. This robust likelihood procedure can be easily implemented by using any statistical software that provides naïve and sandwich covariance matrices for regression parameter estimates. Simulations and real data analyses are used to demonstrate the efficacy of this parametric robust method.     

Modeling asset returns with alternative stable distributions *

In the 1960's Benoit Mandelbrot and Eugene Fama argued strongly in favor of the stable Paretian distribution as a model for the unconditional distribution of asset returns. Although a substantial body of subsequent empirical studies supported this position, the stable Paretian model plays a minor role in current empirical work.

While in the economics and finance literature stable distributions are virtually exclusively associated with stable Paretian distributions, in this paper we adopt a more fundamental view and extend the concept of stability to a variety of probabilistic schemes. These schemes give rise to alternative stable distributions, which we compare empirically using S&P 500 stock return data. In this comparison the Weibull distribution, associated with both the nonrandom-minimum and geometric-random summation schemes dominates the other stable distributions considered-including the stable Paretian model.     

A Symposium on Unemployment Statistics

Separate Poisson distributions were evaluated via several hypotheses tests for each of the 16 teams in the National Hockey League using 1973–74 goals for and goals against both home and away. After examining independence of goals for and goals against, they in turn were used to explain order of finish for the 16 teams. The results were quite surprising.     

Nonnormality of Linear Combinations of Normal Random Variables

Hamedani and Tata (1975) showed that the bivariate normal distribution is determined uniquely by any countably infinite collection of distinct linear combinations of the variables and by no finite number of them. It is shown here that this characterization of bivariate normal distribution cannot be extended to the multivariate case. More specifically, it is shown that the multivariate normality of subsets (r < n) of the normal variables X ₁, X ₂, …, X_n together with the normality of an infinite number of linear combinations of them do not guarantee the joint normality of these variables.     

民事诉讼证明责任分配规则实证分析

由于我国当事人取证能力的薄弱,法官倾向于将客观证明责任转化为主观证明责任来加以使用,笔者得出客观证明责任的重要性更多地体现在对当事人在诉讼过程中取证方向的指引。而由于我国证明责任分配规则在法律中规定的极为不明确,导致二审改判率的上升,因此笔者主张在实体法的制定过程中,要注意将证明责任的分配规则规定得更为明确,给法官以明确的指引。     

供应链利益分配研究--资源与贡献率的分配思路与框架

建立一种有效的分配机制,不仅有利于实现供应链整个资源的有效配置,提高供应链的效率,而且也有利于保证供应链的稳定性.本文主要从供应链的资源构成及其对供应链的贡献程度探讨了供应链利益分配问题,提出参与供应链各个主体的利益分配思路与框架.     

高原山区人口分布特征及其主要影响因素——基于毕节地区的Panel Data计量模型分析

本文基于1987～2007年毕节地区八个县市经济、社会和资源环境方面的面板数据,考察了资源环境、经济水平和社会发展等因素对毕节人口分布变动的影响。研究发现,毕节各县市的人口总量和人口密度稳步增加,呈现协同式的增长态势,但各县市之间增长速度快慢不一,显示了区域间的差异;自然环境因素对人口地域分布变动的影响日趋减弱,但是减小的幅度并不大,说明了自然环境因素对人口分布变动的影响是根深蒂固的;经济水平和社会发展因素对人口密度变动的影响越来越大,其中尤以人均GDP和医疗条件变量更为显著;就人口密度的动态变化影响而言,除了受资源环境、社会经济发展因素的共同影响之外,毕节各个县市还表现出其个体显著差异的特征。