基于阶段划分的企业主动碳减排创新策略实施研究

基于环境策略在被动阶段和主动阶段的不同,且一些企业已启动主动减排阶段的产品创新策略。本文在碳减排阶段划分的基础上,对企业主动碳减排创新策略实施进行研究,引入碳排放交易制度及政府补贴激励,构建了政策驱动下的企业主动碳减排成本收益模型和行业成本收益模型。以矩阵正定性判定企业碳减排是否存在最优策略,同时探讨该最优策略能否实现行业帕累托最优以及如何实现。研究表明,企业主动碳减排创新策略存在最优,企业对碳减排策略的投入随着其相应减排效果系数、减排收益系数与碳排放交易下政府超额补贴系数的增加而加大;行业实现帕累托最优需要政府激励政策引导,且碳排放交易下政府超额补贴系数为行业内定值,随行业内各企业减排效果与创新收益的增加而减少。此外,根据实地调研和相关文献的数据,对模型中的各项参数进行赋值,并以水泥企业为例,通过典型算例分析和关键参数灵敏度分析进行模型有效性验证。算例分析结果证实了创新收益和政府碳排放交易下的补贴激励是企业主动碳减排的关键因素。本文从阶段划分的视角对碳减排问题进行尝试性研究,可为企业主动碳减排创新策略的实施提供决策依据,同时也为政府政策制定提供参考。此外在政府引导企业碳减排帕累托改进过程中,应保障企业碳减排效率在同一水平,创新力较强的企业,减排量相应较大,从而实现碳减排的帕累托最优。     

Some linear and nonlinear rank tests for competing risks models

Using the methods of asymptotic decision theory asymptotically optimal for translation and scale families as well as for certian nonparmetric families. Moreover, two new classes of nonlinear rank tests are introduced. These tests are designed for detecting either “ omnibus alternatives ” or “ one sided alternatives of trend ”. Under the null hypothesis of randomness all tests are distribution - free. The asymptotic distributions of the test statistics are derived under contiguous alternatives.     

Detection of multiple change-points in multivariate data

The statistical analysis of change-point detection and estimation has received much attention recently. A time point such that observations follow a certain statistical distribution up to that point and a different distribution – commonly of the same functional form but different parameters after that point – is called a change-point. Multiple change-point problems arise when we have more than one change-point. This paper develops a method for multivariate normally distributed data to detect change-points and estimate within-segment parameters using maximum likelihood estimation.     

英语多元WH-问句移位优先权的优选分析

在优选论框架下研究了英语多元wh-问句四种移位优先权现象。通过语料分析修改了G rim shaw对wh-移位研究中的两点不足,最终确立了wh-移位的五个制约条件及其层级排列体系。研究表明,优选论能够为英语中四种优先权现象提供比较一致的解释,而且能使一元和多元wh-问句移位问题在优选论框架下达到统一。     

On Universal Optimality of Circular Weakly Neighbor Balanced Designs Under an Interference Model

In this article, the optimal design problem in a fixed effects interference model with left-neighbor effects is studied. It is known (Druilhet, 1999 Druilhet , P. ( 1999 ). Optimality of circular neighbor balanced designs . J. Statist. Plann. Infer. 81 : 141 – 152 .[Crossref], [Web of Science ®] , [Google Scholar]) that circular neighbor balanced designs (CNBDs) are universally optimal in such a model. We prove the universal optimality of circular weakly neighbor balanced designs (CWNBDs), which require a smaller number of blocks than CNBDs. CWNBDs with the number of blocks smaller than the number of treatments belong to the class of partially neighbor balanced designs (PNBDs) defined by Wilkinson et al. (1983 Wilkinson , G. N. , Eckert , R. , Hancock , T. W. , Mayo , O. ( 1983 ). Nearest neighbour (NN) analysis of field experiments . J. Roy. Statist. Soc. Ser. B 45 : 151 – 210 . [Google Scholar]). We give a construction method for some CWNBDs, with examples.     

Extension and necessity of Cheng and Wu conditions

Repeated Measurement Designs, with two treatments, n (experimental) units and p periods are examined. The model examined is with uncorrelated observations following a continuous distribution with constant variance and the parameters of interest are (i) the difference of direct effects and (ii) the difference of residual effects. In this paper (a) the difference of Universal optimality and Φ-optimality is clarified and (b) the sufficient conditions of Cheng and Wu (1980) are extended to include the case n=2 mod 4, p even, (c) also it is shown that these conditions are also necessary for Φ-optimality for estimating direct as well as residual effects, and (d) a method is proposed to construct Φ-optimal designs and examples are given when n even and p=3, n=0 mod 4 and p=4, n=2 mod 4 and p=4. In the last case the estimated parameters in the optimal design are correlated.     

ON EMPIRICAL BAYES STOPPING TIMES

We consider the empirical Bayes decision theory where the component problems are the optimal fixed sample size decision problem and a sequential decision problem. With these components, an empirical Bayes decision procedure selects both a stopping rule function and a terminal decision rule function. Empirical Bayes stopping rules are constructed for each case and the asymptotic behaviours are investigated.     

The Construction of Optimal Balanced Incomplete Block Designs When Adjacent Observations are Correlated

An algorithm is described for the optimal rearrangement of the treatments within each block of a Balanced Incomplete Block Design when a specified “nearest neighbour” correlation structure exists among observations from plots in the same block. The procedure uses results obtained by Kiefer & Wynn (1981). Designs obtained using the algorithm are found to compare favourably with those produced by combinatorial methods given in Cheng (1983). The algorithm produces optimal designs for all BIBD parameter sets, including those not covered by the results of Kiefer & Wynn or Cheng.     

A-Optimal Block Designs with Additional Singly Replicated Treatments

Block designs to which have been added a number of singly-replicated treatments, known as secondary treatments, are particularly useful for experiments where only small amounts of material are available for some treatments, for example new plant varieties. The designs are of particular use in the microarray situation. Such designs are known as 'augmented designs'. This paper obtains the properties of these designs and shows that, with an equal number of secondary treatments in each block, the A-optimal design is obtained by using the A-optimal design for the original block design. It develops formulae for the variance of treatment comparisons, for both the primary and the secondary treatments. A number of examples are used to illustrate the results.