On the shape of the cross-ratio function in bivariate survival models induced by truncated and folded normal frailty distributions

In shared frailty models for bivariate survival data the frailty is identifiable through the cross-ratio function (CRF), which provides a convenient measure of association for correlated survival variables. The CRF may be used to compare patterns of dependence across models and data sets. We explore the shape of the CRF for the families of one-sided truncated normal and folded normal frailty distributions.     

Minimax estimation for the bounded mean of a bivariate normal distribution

A bivariate normal distribution is considered whose mean lies in an equilateral triangle. We show by a convexity argument that the three point prior having mass 1/3 at each of the edges is least favourable if the length of a side of the equilateral triangle is less than or equal to . Thus the corresponding Bayes estimator is minimax in that case. Numerical studies are given as well.     

A Bayesian test of the product cycle hypothesis applied to Japanese crude steel production

It is postulated that the product cycle of crude steel production may be observed as a gradual shift in the time trend parameter in the family of the CES production functions. Quarterly data from 1957 to 1973 are used for the empirical test. Posterior pdf's for the join point as well as for the adjustment parameter are derived, and they indicate that Japanese crude steel production passed from the new to standardized product stage between 1968 and 1972. With the arrival of the standardized state it is noted that the industry has become less competitive.     

Natural conjugate priors for the instrumental variables regression model applied to the Angrist–Krueger data

We propose a natural conjugate prior for the instrumental variables regression model. The prior is a natural conjugate one since the marginal prior and posterior of the structural parameter have the same functional expressions which directly reveal the update from prior to posterior. The Jeffreys prior results from a specific setting of the prior parameters and results in a marginal posterior of the structural parameter that has an identical functional form as the sampling density of the limited information maximum likelihood estimator. We construct informative priors for the Angrist–Krueger [1991. Does compulsory school attendance affect schooling and earnings? Quarterly Journal of Economics 106, 979–1014] data and show that the marginal posterior of the return on education in the US coincides with the marginal posterior from the Southern region when we use the Jeffreys prior. This result occurs since the instruments are the strongest in the Southern region and the posterior using the Jeffreys prior, identical to maximum likelihood, focusses on the strongest available instruments. We construct informative priors for the other regions that make their posteriors of the return on education similar to that of the US and the Southern region. These priors show the amount of prior information needed to obtain comparable results for all regions.     

Modifications of the Farlie-Gumbel-Morgenstern distributions. A tough hill to climb

Polynomial-type single parameter extensions of the Farlie-Gumbel Morgenstern bivariate distributions are studied. It is shown that by means of these structures the positive correlation between the marginal distributions can be increased up to ≈.39 while the maximal negative correlation remains . Received: May 1998     

浅析我国网上药店发展所面临的机遇和挑战

近几年,我国网上购物发展迅速,为网上药店的发展奠定了良好的基础。文章首先描述网上药店所面临的一系列机遇,随后介绍其目前存在的挑战,最后针对这些挑战提出了几点改善建议。     

箱式变电所在住宅小区中设计应注意的问题

箱式变电所以其显著优点,在住宅小区建设(改造)中得到推广应用。文章以南宁市某住宅小区为例,论述箱式变电所设计中应注意的问题。     

箱式变电所在住宅小区中设计应注意的问题

箱式变电所以其显著优点,在住宅小区建设（改造）中得到推广应用。文章以南宁市某住宅小区为例,论述箱式变电所设计中应注意的问题。     

箱式变电所在住宅小区中设计应注意的问题

箱式变电所以其显著优点,在住宅小区建设(改造)中得到推广应用.文章以南宁市某住宅小区为例,论述箱式变电所设计中应注意的问题.     

拓宽城市土地储备资金渠道的几种思路

土地储备制度的实施对加强城市政府对土地市场的宏观调控,控制土地供给总量,规范土地市场发展起到了明显的作用,但随着实施过程的深入,目前也遇到了一些制约因素,其中最主要的就是土地储备资金问题.本文分析了目前土地储备资金渠道的局限性,然后有针对性地提出了几种拓宽资金渠道的新思路.     

A bootstrap algorithm for testing cointegration rank in VAR models in the presence of stationary variables

In this paper, a bootstrap algorithm for a reduced rank vector autoregressive (VAR) model which also includes stationary regressors, is analyzed. It is shown that the bootstrap distribution for estimating the rank converges to the distribution derived from the usual asymptotic framework. Because the asymptotic distribution will typically depend on unknown parameters, bootstrap distributions are of considerable interest in this context. The result of an application and some Monte Carlo experiments are also presented.     

A property of Stein's estimator for the mean of a multivariate normal distribution

A uniform bound on the risk (under squared error loss) of Stein's estimator Ψ₁ for the mean of the multivariate normal distribution is given. Using the bound, the asymptotic behaviour of the risk of Ψ₁ under a Bayesian assumption is obtained.     

A control function approach for testing the usefulness of trending variables in forecast models and linear regression

Many predictors employed in forecasting macroeconomic and finance variables display a great deal of persistence. Tests for determining the usefulness of these predictors are typically oversized, overstating their importance. Similarly, hypothesis tests on cointegrating vectors will typically be oversized if there is not an exact unit root. This paper uses a control variable approach where adding stationary covariates with certain properties to the model can result in asymptotic normal inference for prediction regressions and cointegration vector estimates in the presence of possibly non-unit root trending covariates. The properties required for this result are derived and discussed.     

Information theoretic methods of spatial model building: A guide to the unbiased estimation of the form of probability distributions2

The methods of maximum entropy and minimum information are employed in order to provide unbiased a priori estimates of the form of probability distributions, given limited prior knowledge. These a priori estimates, in turn, can be cast in the form of theoretical models of the phenomena of interest; models to be tested against real world data. As such, the methods of maximum entropy and minimum information have relevance to any scientific or social-scientific discipline wherein the mathematical modelling of probability distributions is a concern. At the same time, however, the methods are mathematically difficult and conceptually demanding. This paper therefore presents a pedagogic introduction to the methods of maximum entropy and minimum information in the hope of making them more accessible to those social scientists who might find them relevant to their work. Using a simple example, the paper works through the two methods, one at a time, adding more and more information to the estimation problem as the discussion proceeds. The focus herein is a geographic one, yet the example employed is easily transferable to alternative contexts.     

Multivariate analysis of coffee images: A study in the simultaneous display of multivariate quantitative and qualitative variables for several assessors

The paper discusses a small image study in which seven assessors judge nine brands of coffee in terms of six quantitative variables and five categorical variables. Generalised Procrustes Analysis and Generalised Biplots are combined to display simultaneously information on the brands and on both quantitative and categorical variables. An outline is given of the methodology.