解码“中国经济增长”

消费是人类经济增长最初也是最终的目的，单纯为了经济增长速度、为了增加就业、为了出口创汇等，可能脱离经济发展的消费目的，未必有利于真正的经济增长。新时期中国理想的经济增长必须考虑以下六个制约因素，即居民增长的消费需求、资源的供给、环境容量、国际竞争力、科技创新和制度。关键是突出消费作为增长的目的，抛弃狭隘的速度思维，将环境保护放在首位，以分配公平为前提，建立有责任约束的经济增长机制。     

The Condom Fairy program: A novel mail-order service for condoms and sexual health supplies

Abstract

Objective: In recent years college health professionals have used a variety of innovative strategies to increase availability and accessibility of condoms and safer sex products. The purpose of this study is to evaluate the efficacy and efficiency of a mail-order delivery program titled the Condom Fairy. Participants: Seven hundred thirty-three students (63.4% women, 86.1% heterosexual, and 59.2% Caucasian) completed a questionnaire assessing their overall experience with the program. Methods: Participants completed a 60 item questionnaire 30?days after receiving condoms and safer sex products. Results: Overall, 46,980 condoms were distributed over a six semester period. Almost all of the participants (97.4%) reported they ordered male condoms while 58.0% ordered sexual lubricant, 11.1% female condoms, and 10.2% latex dams. Nearly than three-quarters (73.9%) of participants reported they used the condoms provided. Conclusions: Findings support the implementation of innovative mail-in condom and safer sex product programs on college campuses.     

Inverse gaussian accelerated test models based on cumulative damage

The failure of a system under environmental stress often can be described by an accelerated test model which incorporates the environmental variable L. Here, the failure of such a system at environmental level L is modeled as the first passage of accumulated damage to a critical threshold value. Assuming a discrete additive damage model leads to a Birnbaum–Saunders-type distribution for the failure time which can be closely approximated by an inverse Gaussian-type model. However, if a continuous damage model based on a Gaussian process is assumed, a more general family of inverse Gaussian accelerated test models is obtained. Three sets of failure data are discussed to illustrate the usefulness of this general family.     

A non-iterative posterior sampling algorithm for linear quantile regression model

In this article, a non-iterative posterior sampling algorithm for linear quantile regression model based on the asymmetric Laplace distribution is proposed. The algorithm combines the inverse Bayes formulae, sampling/importance resampling, and the expectation maximization algorithm to obtain independently and identically distributed samples approximately from the observed posterior distribution, which eliminates the convergence problems in the iterative Gibbs sampling and overcomes the difficulty in evaluating the standard deviance in the EM algorithm. The numeric results in simulations and application to the classical Engel data show that the non-iterative sampling algorithm is more effective than the Gibbs sampling and EM algorithm.     

A multiple warm standby δ-shock system with a repairman having multiple vacations

In this article, a warm standby n-unit system is studied. The system is operational as long as there is one unit normal. The unit online, which has a lifetime distribution governed by a phase-type distribution, is also attacked by a shock from some external causes. Assume that shocks arrive according to a Poisson process. Whenever an interarrival time of shock is less than a threshold, the unit online fails. The lifetimes of the units in warm standby is exponentially distributed. A repairman who can take multiple vacations repairs the failed units based on the “first-in-first-out” rule. The repair times and the vacation times of repairman are governed by different phase-type distributions. For this system, the Markov process governing the system is constructed. The system is studied in a transient and stationary regime; the availability, the reliability, the rates of occurrence of the different types of failures, and the working probability of the repairman are calculated. A numerical application is performed to illustrate the calculations.     

Shared frailty model based on reversed hazard rate for left censored data

Frailty models are used in the survival analysis to account for the unobserved heterogeneity in the individual risks to disease and death. To analyze the bivariate data on related survival times (e.g., matched pairs experiments, twin or family data), the shared frailty models were suggested. In this article, we introduce the shared gamma frailty models with the reversed hazard rate. We develop the Bayesian estimation procedure using the Markov chain Monte Carlo (MCMC) technique to estimate the parameters involved in the model. We present a simulation study to compare the true values of the parameters with the estimated values. We apply the model to a real life bivariate survival dataset.     

Comparison between method of moments and entropy regularization algorithm applied to parameter estimation for mixed-Weibull distribution

Mixed-Weibull distribution has been used to model a wide range of failure data sets, and in many practical situations the number of components in a mixture model is unknown. Thus, the parameter estimation of a mixed-Weibull distribution is considered and the important issue of how to determine the number of components is discussed. Two approaches are proposed to solve this problem. One is the method of moments and the other is a regularization type of fuzzy clustering algorithm. Finally, numerical examples and two real data sets are given to illustrate the features of the proposed approaches.     

中国商品流通现代化的模糊综合评价研究

完善了商品流通现代化指标体系,并运用模糊综合法将商品流通现代化指标转换成了指数。研究发现商品流通现代化水平与其区域位置、总体经济实力密切相关,且受到产业结构的影响。同时,通过基于指数的聚类分析得到如下结论:"率先发展型区域"要抓住历史机遇,培养创新型人才,保持领先地位;"积极追赶型区域"要发挥地理优势,打破省之间、行业和部门之间、所有制之间的界限,积极参与各种区域经济合作;"流通欠发达型区域"要进一步推进和实施西部大开发战略,推进物流现代化。     

Classical estimation of hazard rate and mean residual life functions of Pareto distribution

Abstract

In this paper we find the maximum likelihood estimates (MLEs) of hazard rate and mean residual life functions (MRLF) of Pareto distribution, their asymptotic non degenerate distribution, exact distribution and moments. We also discuss the uniformly minimum variance unbiased estimate (UMVUE) of hazard rate function and MRLF. Finally, two numerical examples with simulated data and real data set, are presented to illustrate the proposed estimates.     

On the construction of optimal experimental designs: a penalty approach

Tn optimal experimental design theory there are well-known situations, in which additional constraints are implied to the design set. These constraints destroy in general the simplex structure of the set of feasible points of the design set. Thus the available iteration procedures for the unrestricted case are no longer applicable.

In this paper a penalty approach is suggested which transforms the restricted problem to the unrestricted case and allows the application of well-known algorithms such as the Fedorov-Wynn-type or the projected gradient procedure.