Binary Event String Analysis: A Compact Numerical Representation of the Event Tree

While the event tree is a useful diagrammatic aid to an appreciation of various event sequence possibilities, it is of a nature that suggests no obvious manner in which the associated probability data may be compiled as computer input. Here, we propose a complementary numerical representation of scenario possibilities which incorporates probability data in a succinct fashion. While its mnemonic properties facilitate the logical development of a system's characteristics, its compactness and unambiguity permit its utilization directly as computer input.     

Tree-structured subgroup analysis for censored survival data: Validation of computationally inexpensive model selection criteria

The performance of computationally inexpensive model selection criteria in the context of tree-structured subgroup analysis is investigated. It is shown through simulation that no single model selection criterion exhibits a uniformly superior performance over a wide range of scenarios. Therefore, a two-stage approach for model selection is proposed and shown to perform satisfactorily. Applied example of subgroup analysis is presented. Problems associated with tree-structured subgroup analysis are discussed and practical solutions are suggested.     

清代树木栽培技术及相关文献探析

中国的树木栽培技术源远流长,曾取得过辉煌的成就。清朝时期在对前人的树木栽培技术进行系统总结和归纳的基础上,结合树木栽培的生产实践,编纂出版了几部学术价值高、影响大、实用性强的文献资料。同时这一时期在植物嫁接成活的生理机制研究、嫁接技术、树木移栽、良种选育与新品种培育、实生苗繁殖技术等方面取得了一定的成就,使清代的树木栽培技术更加完善和成熟。     

大学校园中植物多样性调查———以福州地区为例简

当前大学校园环境的塑造广泛引起关注,一个大学校园环境塑造的好坏与其植物配置密切相关。对福州地区十个校园环境的植物进行调查,对其多样性进行总结。为植物配置、植材选择及校园环境塑造给予一定的参考及建议。     

Multi-Step Classification Trees

Many algorithms originated from decision trees have been developed for classification problems. Although they are regarded as good algorithms, most of them suffer from loss of prediction accuracy, namely high misclassification rates when there are many irrelevant variables. We propose multi-step classification trees with adaptive variable selection (the multi-step GUIDE classification tree (MG) and the multi-step CRUISE classification tree (MC) to handle this problem. The variable selection step and the fitting step comprise the multi-step method.

We compare the performance of classification trees in the presence of irrelevant variables. MG and MC perform better than Random Forest and C4.5 with an extremely noisy dataset. Furthermore, the prediction accuracy of our proposed algorithm is relatively stable even when the number of irrelevant variables increases, while that of other algorithms worsens.     

Parameter estimation of nonlinear mixed-effects models using first-order conditional linearization and the EM algorithm

Nonlinear mixed-effects (NLME) models are flexible enough to handle repeated-measures data from various disciplines. In this article, we propose both maximum-likelihood and restricted maximum-likelihood estimations of NLME models using first-order conditional expansion (FOCE) and the expectation–maximization (EM) algorithm. The FOCE-EM algorithm implemented in the ForStat procedure SNLME is compared with the Lindstrom and Bates (LB) algorithm implemented in both the SAS macro NLINMIX and the S-Plus/R function nlme in terms of computational efficiency and statistical properties. Two realworld data sets an orange tree data set and a Chinese fir (Cunninghamia lanceolata) data set, and a simulated data set were used for evaluation. FOCE-EM converged for all mixed models derived from the base model in the two realworld cases, while LB did not, especially for the models in which random effects are simultaneously considered in several parameters to account for between-subject variation. However, both algorithms had identical estimated parameters and fit statistics for the converged models. We therefore recommend using FOCE-EM in NLME models, particularly when convergence is a concern in model selection.     

基于Probit模型的果农技术采用行为研究

对农户技术采用行为影响因素的研究可以为技术扩散过程的优化与调控提供科学依据。选择两个果业种植专业村,对影响农户技术采用行为的因素进行了实际调查,并利用Probit模型进行了验证和确认。综合分析认为,农户科技文化素质、政府推广部门职能的发挥程度、空间距离、区域自然条件、中介组织的发育程度、技术本身的属性等是影响农户技术采用行为的主要因素,并提出了相关的政策建议。     

A General Model of Some Inverse Combinatorial Optimization Problems and Its Solution Method Under l ∞ Norm

This paper proposes an optimization model and shows that most inverse combinatorial optimization problems so far discussed can be fit into this model as special cases. We propose a Newton-type algorithm for this model under l norm. This algorithm can solve the model in strongly polynomial time if the subproblem involved is solvable in strongly polynomial time for any fixed value of the parameter appearing in the subproblem, and it is shown that most particular inverse optimization problems encountered are this kind. Therefore, through this paper we show that a large group of inverse optimization problems can be handled in a uniform way and solved in strongly polynomial time.     

基于实物期权法的矿区生态补偿额核算研究——以湖南花垣锰矿区为例

确定补偿资标准是矿产开发生态补偿机制构建的关键,也是难点。实物期权二叉树模型能比较精确地计算出项目预期收益,而项目预期收益与实际收益的差额就是生态补偿额中的发展机会成本。运用此模型对湖南花垣县生态补偿额度中发展机会成本的年补偿额进行核算得知,目前矿区生态补偿额的征收标准过低,远远不能满足生态补偿的要求,因此,国家应增加生态补偿资金的拨付或加大税费征收力度,以达到对矿产资源的有偿使用和合理利用。