Resource allocation and project selection: Control of r & d under dynamic process of data improvement

This paper deals with the problem of optimal control of R&D. The fundamental aspects of this problem are viewed as: uncertainty about economic parameters of new technology (or new activity, e.g. a search for new oil fields) explored by a group of parallel projects attempting to make advances in this technology as well as improve economic data; allocation of investments among rival projects under a given total budget; timing of the ultimate selection of new technology (activity) according to the most successful project. The process of data improvement (PDI) is described as a (random) process of reducing the intervals of uncertainty, the rate of data improvement being controlled, in effect, by the investment policy. A stationary dynamic model with infinite horizon of planning and with the criterion of total discounted costs is developed. The model is carefully investigated from the economic point of view, and some new effects are discovered. It is demonstrated that uncertainty may be the source of additional gain; the bigger the initial uncertainty, the bigger the gain may be under optimal control. This effect is based on PDI, the economic background of which is presented as multiplication of the expected gain over time, which is typical for the classical macromodels of economics.Optimal continuous control is constructed at every time moment, and answers to two main questions are given:(1) either to prolong R & D or to make ultimate selection of one project, (2) how to allocate resources among the rival projects in the case of R&D prolongation. The last question is answered on the basis of profitability indices that relate efficiencies of PDI for particular projects to the costs of information.     

Analyzing cross-sectional and longitudinal lung-function measurements: The effects of age

The problem of interpreting lung-function measurements in industrial workers is examined. The data under discussion pertain to FEV₁ and FVC measurements in smoking and in nonsmoking groups of grain-elevator workers in British Columbia and of workers in Vancouver City Hall. Initial observations have now been enriched by longitudinal follow up data on the same groups after three and after six years. It is shown that interesting selection phenomena, favouring “fit” individuals, take place over time, with regard both to lung symptoms and lung functions. Thus cross-sectional and longitudinal studies refer to somewhat different populations. It also appears that longitudinal studies are considerably more sensitive to identifying cumulative lung damage than are corresponding cross-sectional studies. The nonlinearity of the effect of age on lung functions is noted in the longitudinal data in a number of cases, lending support to the hypothesis of association between quadratic age effect and cumulative exposure to lung insults.     

Learning a multivariate Gaussian mixture model with the reversible jump MCMC algorithm

This paper is a contribution to the methodology of fully Bayesian inference in a multivariate Gaussian mixture model using the reversible jump Markov chain Monte Carlo algorithm. To follow the constraints of preserving the first two moments before and after the split or combine moves, we concentrate on a simplified multivariate Gaussian mixture model, in which the covariance matrices of all components share a common eigenvector matrix. We then propose an approach to the construction of the reversible jump Markov chain Monte Carlo algorithm for this model. Experimental results on several data sets demonstrate the efficacy of our algorithm.     

A review of optimal designs in survey sampling

Results in five areas of survey sampling dealing with the choice of the sampling design are reviewed. In Section 2, the results and discussions surrounding the purposive selection methods suggested by linear regression superpopulation models are reviewed. In Section 3, similar models to those in the previous section are considered; however, random sampling designs are considered and attention is focused on the optimal choice of π_j. Then in Section 4, systematic sampling methods obtained under autocorrelated superpopulation models are reviewed. The next section examines minimax sampling designs. The work in the final section is based solely on the randomization. In Section 6 methods of sample selection which yield inclusion probabilities π_j = n/N and π_ij = n(n - 1)/N(N - 1), but for which there are fewer than _NC_n possible samples, are mentioned briefly.     

论高校系级领导班子的选配和总体素质的提高

系一级单位是高等学校中最基本最重要的中层单位，系级领导班子建设是高等学校党的建设一项关乎全局的工作内容。本文从大胆选拔和启用德才兼备的年轻干部和优秀教师、狠抓系级领导骨干的素质提高、在管理工作的实践中培养管理人才诸方面，论述了高校在新老交替的过程中，应努力搞好系级领导班子建设，以确保其在组织上、思想作风上和制度上的连续性、稳定性和创新性，生机勃勃地迈向新世纪     

SELECTING "DEMONSTRABLY BEST" OR "DEMONSTRABLY WORST" EXPONENTIAL POPULATIONS

Consider k independent observations Y_i (i= 1,., k) from two-parameter exponential populations _i with location parameters μ and the same scale parameter If the μ_i are ranked as consider population as the “worst” population and II_p(k) as the “best” population (with some tagging so that p{) and p(k) are well defined in the case of equalities). If the Y_i are ranked as we consider the procedure, “Select provided Y_R(k) Y_r(k) is sufficiently large so that is demonstrably better than the other populations.” A similar procedure is studied for selecting the “demonstrably worst” population.     

Identification of non-linear additive autoregressive models

Summary.  We propose a lag selection method for non-linear additive autoregressive models that is based on spline estimation and the Bayes information criterion. The additive structure of the autoregression function is used to overcome the 'curse of dimensionality', whereas the spline estimators effectively take into account such a structure in estimation. A stepwise procedure is suggested to implement the method proposed. A comprehensive Monte Carlo study demonstrates good performance of the method proposed and a substantial computational advantage over existing local-polynomial-based methods. Consistency of the lag selection method based on the Bayes information criterion is established under the assumption that the observations are from a stochastic process that is strictly stationary and strongly mixing, which provides the first theoretical result of this kind for spline smoothing of weakly dependent data.     

Small area estimates for cross-classifications

Summary.  We develop a class of log-linear structural models that is suited to estimation of small area cross-classified counts based on survey data. This allows us to account for various associ- ation structures within the data and includes as a special case the restricted log-linear model underlying structure preserving estimation. The effect of survey design can be incorporated into estimation through the specification of an unbiased direct estimator and its associated covariance structure. We illustrate our approach by applying it to estimation of small area labour force characteristics in Norway.     

Clustering objects on subsets of attributes (with discussion)

Summary.  A new procedure is proposed for clustering attribute value data. When used in conjunction with conventional distance-based clustering algorithms this procedure encourages those algorithms to detect automatically subgroups of objects that preferentially cluster on subsets of the attribute variables rather than on all of them simultaneously. The relevant attribute subsets for each individual cluster can be different and partially (or completely) overlap with those of other clusters. Enhancements for increasing sensitivity for detecting especially low cardinality groups clustering on a small subset of variables are discussed. Applications in different domains, including gene expression arrays, are presented.     

直面政治主体的历史选择时限

考察一些老党、大党在 2 0世纪最后几十年被历史所淘汰的根源 ,可以看出 :政治主体的历史选择时限由执政根基中起重要作用的经济因素所决定 ,除此之外 ,政党的内聚力和社会动员功能也不容忽视。