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.     

Estimation and Inference Procedures for Semiparametric Distribution Models with Varying Linear‐Index

More flexible semiparametric linear‐index regression models are proposed to describe the conditional distribution. Such a model formulation captures varying effects of covariates over the support of a response variable in distribution, offers an alternative perspective on dimension reduction and covers a lot of widely used parametric and semiparameteric regression models. A feasible pseudo likelihood approach, accompanied with a simple and easily implemented algorithm, is further developed for the mixed case with both varying and invariant coefficients. By justifying some theoretical properties on Banach spaces, the uniform consistency and asymptotic Gaussian process of the proposed estimator are also established in this article. In addition, under the monotonicity of distribution in linear‐index, we develop an alternative approach based on maximizing a varying accuracy measure. By virtue of the asymptotic recursion relation for the estimators, some of the achievements in this direction include showing the convergence of the iterative computation procedure and establishing the large sample properties of the resulting estimator. It is noticeable that our theoretical framework is very helpful in constructing confidence bands for the parameters of interest and tests for the hypotheses of various qualitative structures in distribution. Generally, the developed estimation and inference procedures perform quite satisfactorily in the conducted simulations and are demonstrated to be useful in reanalysing data from the Boston house price study and the World Values Survey.     

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。     

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。     

论《醒世姻缘传》的树形结构

《醒世姻缘传》的结构神似树形,因果观是树形结构之根,晁源和狄希陈的前生后世的婚姻是树形结构的主干,晁夫人的后半世是树形结构的次干,诸多大小轶事构成树形结构的枝叶。依托树形结构,整部小说以惧内故事为主要讲述对象,展示明代中后期乡村及城市中下层各色人物和社会生活,其结构颇具特色。     

樟树意象的文化象征

樟树作为文化符号所遭遇的古冷今热的现象很值得研究。作为自然生长的南方树种,其实用价值表现多多,但是在芬芳比德、植物象征极为盛行的古代,樟树却没能获得应有的文化品质,这与其不幸生长在非政治中心的南方区域且隐居深山幽谷有关。至而今,尤其是近十余年来,樟树已被37个地级市选作市树,其符号价值迅速飙升,而主要的实用价值反而在无意间被忽略了。樟树作为市树确实让城市更美了,不过,它们展示的只是其亮丽的外表。     

喷树增产耐贮剂对沙糖桔树上及采后的保鲜效果

于沙糖桔果实转色期喷施＂喷树增产耐贮剂＂,可提高采前保果率、总糖、可溶性固形物和谷胱甘肽的含量,显著降低因干冷和湿冷引起的伤果和落果率.该处理可显著减少采后贮藏期总糖、可溶性固形物和水分的损失,减少烂果率,有助于维持果品的产量和质量.     

北京大学校园内植树碑考证

在北京大学未名湖旁有两块植树碑,一块是清朝乾隆皇帝丁未年（1788）所立,一块是民国十一年（1922）燕京大学教育系壬戌班所立,本文对这两块碑的碑文进行了考证。     

Testing for order among K populations: theory and examples

Testing for stochastic order among K populations is a common and important problem in statistical practice. It arises in the analysis of both planned experiments and observational studies. The authors develop a new nonparametric test for order among K populations that can accommodate any stochastic ordering. The test is based on a maximally selected chi‐bar‐square statistic. The authors find its limiting distribution and use simulations to derive critical values. Three important examples are used to illustrate the applicability of the general method. The authors find that the new tests outperform the existing methods in many practical cases. The Canadian Journal of Statistics 38: 97–115; 2010 © 2009 Statistical Society of Canada     

Parallelizing computation of expected values in recombinant binomial trees

Recombinant binomial trees are binary trees where each non-leaf node has two child nodes, but adjacent parents share a common child node. Such trees arise in option pricing in finance. For example, an option can be valued by evaluating the expected payoffs with respect to random paths in the tree. The cost to exactly compute expected values over random paths grows exponentially in the depth of the tree, rendering a serial computation of one branch at a time impractical. We propose a parallelization method that transforms the calculation of the expected value into an embarrassingly parallel problem by mapping the branches of the binomial tree to the processes in a multiprocessor computing environment. We also discuss a parallel Monte Carlo method and verify the convergence and the variance reduction behavior by simulation study. Performance results from R and Julia implementations are compared on a distributed computing cluster.