Statistical inference based on generalized Lindley record values

This paper addresses the problems of frequentist and Bayesian estimation for the unknown parameters of generalized Lindley distribution based on lower record values. We first derive the exact explicit expressions for the single and product moments of lower record values, and then use these results to compute the means, variances and covariance between two lower record values. We next obtain the maximum likelihood estimators and associated asymptotic confidence intervals. Furthermore, we obtain Bayes estimators under the assumption of gamma priors on both the shape and the scale parameters of the generalized Lindley distribution, and associated the highest posterior density interval estimates. The Bayesian estimation is studied with respect to both symmetric (squared error) and asymmetric (linear-exponential (LINEX)) loss functions. Finally, we compute Bayesian predictive estimates and predictive interval estimates for the future record values. To illustrate the findings, one real data set is analyzed, and Monte Carlo simulations are performed to compare the performances of the proposed methods of estimation and prediction.     

存款准备金率政策的传导机制——基于商业银行资产负债管理的微观结构分析

由于经济体系中的流动性过剩问题日趋严重,中国人民银行连续上调存款准备金率,以期通过这种重量级的货币政策来收缩银行体系的货币供给,从而有效地控制流动性过剩.存款准备金率政策的最终政策效应,有赖于通过银行体系内部商业银行的资产负债管理行为而达成.然而,这一货币政策传导机制本身充满着诸多相互作用的变量和相应的行为选择.本文就这一问题出发,深入地解析了存款准备金率政策通过商业银行资产负债管理而起作用的内在微观结构.     

影响企业扩张度的因素及其熵描述

通过对影响企业扩张度因素的分析以及熵思想下企业扩张度的重新界定,指出企业扩张必须遵循的原则就是,扩张必须基于自身核心竞争能力等内部基本元素的强弱与外部环境来确定其扩张的规模、速度以及经济范围,以便达到内部熵能最小和持续发展的目的。     

中德婚姻市场供需情况的比较研究

本文从概念、形成机制、度量方法、后果及其解决途径等方面探讨了婚姻挤压问题 ,考虑到婚姻挤压对婚姻寿命、初婚人数及其性别差异的影响而创立了婚姻寿命指数与初婚挤压指数两指标 ,提出了婚姻市场类型的划分标准。通过对中德两国婚姻市场的历史与现状的考察 ,揭示了中德两国婚姻挤压产生的原因、类型、差异和未来的变化趋势 ,并对如何化解中国未来婚姻市场的供求矛盾提出了对策与建议     

ispLSI器件测试板的研制

介绍了MODEL－IE1型ISP和EDA测试板的结构原理及其电路,说明该测试电路的使用方法。     

Factors influencing Soay sheep survival

We present a survival analysis of Soay sheep mark recapture and recovery data. Unlike previous conditional analyses, it is not necessary to assume equality of recovery and recapture probabilities; instead these are estimated by maximum likelihood. Male and female sheep are treated separately, with the higher numbers and survival probabilities of the females resulting in a more complex model than that used for the males. In both cases, however, age and time aspects need to be included and there is a strong indication of a reduction in survival for sheep aged 7 years or more. Time variation in survival is related to the size of the population and selected weather variables, by using logistic regression. The size of the population significantly affects the survival probabilities of male and female lambs, and of female sheep aged 7 or more years. March rainfall and a measure of the North Atlantic oscillation are found to influence survival significantly for all age groups considered, for both males and females. Either of these weather variables can be used in a model. Several phenotypic and genotypic individual covariates are also fitted. The only covariate which is found to influence survival significantly is the type of horn of first-year female sheep. There is a substantial variation in the recovery probabilities over time, reflecting in part the increased effort when a population crash was expected. The goodness of fit of the model is checked by using graphical procedures.     

On the Critical Value Behaviour of Multiple Decision Procedures

In this paper we investigate the asymptotic critical value behaviour of certain multiple decision procedures as e.g. simultaneous confidence intervals and simultaneous as well as stepwise multiple test procedures. Supposing that n hypotheses or parameters of interest are under consideration we investigate the critical value behaviour when n increases. More specifically, we answer e.g. the question by which amount the lengths of confidence intervals increase when an additional parameter is added to the statistical analysis. Furthermore, critical values of different multiple decision procedures as for instance step-down and step-up procedures will be compared. Some general theoretic results are derived and applied for various distributions.     

Correlation in a Bayesian framework

The authors consider the correlation between two arbitrary functions of the data and a parameter when the parameter is regarded as a random variable with given prior distribution. They show how to compute such a correlation and use closed form expressions to assess the dependence between parameters and various classical or robust estimators thereof, as well as between p‐values and posterior probabilities of the null hypothesis in the one‐sided testing problem. Other applications involve the Dirichlet process and stationary Gaussian processes. Using this approach, the authors also derive a general nonparametric upper bound on Bayes risks.     

Bootstrap tests: how many bootstraps?

In practice, bootstrap tests must use a finite number of bootstrap samples. This means that the outcome of the test will depend on the sequence of random numbers used to generate the bootstrap samples, and it necessarily results in some loss of power. We examine the extent of this power loss and propose a simple pretest procedure for choosing the number of bootstrap samples so as to minimize experimental randomness. Simulation experiments suggest that this procedure will work very well in practice.     

On optimal testing for the equality of equicorrelation: An example of loss in power

Sen Gupta (1988) considered a locally most powerful (LMP) test for testing nonzero values of the equicorrelation coefficient of a standard symmetric multivariate normal distribution. This paper constructs analogous tests for the symmetric multivariate normal distribution. It shows that the new test is uniformly most powerful invariant even in the presence of a nuisance parameter, σ². Further applications of LMP invariant tests to several equicorrelated populations have been considered and an extension to panel data modeling has been suggested.