Quantifying uncertainty in the biospheric carbon flux for England and Wales

Summary.  A crucial issue in the current global warming debate is the effect of vegetation and soils on carbon dioxide (CO₂) concentrations in the atmosphere. Vegetation can extract CO₂ through photosynthesis, but respiration, decay of soil organic matter and disturbance effects such as fire return it to the atmosphere. The balance of these processes is the net carbon flux. To estimate the biospheric carbon flux for England and Wales, we address the statistical problem of inference for the sum of multiple outputs from a complex deterministic computer code whose input parameters are uncertain. The code is a process model which simulates the carbon dynamics of vegetation and soils, including the amount of carbon that is stored as a result of photosynthesis and the amount that is returned to the atmosphere through respiration. The aggregation of outputs corresponding to multiple sites and types of vegetation in a region gives an estimate of the total carbon flux for that region over a period of time. Expert prior opinions are elicited for marginal uncertainty about the relevant input parameters and for correlations of inputs between sites. A Gaussian process model is used to build emulators of the multiple code outputs and Bayesian uncertainty analysis is then used to propagate uncertainty in the input parameters through to uncertainty on the aggregated output. Numerical results are presented for England and Wales in the year 2000. It is estimated that vegetation and soils in England and Wales constituted a net sink of 7.55 Mt C (1 Mt C = 10¹² g of carbon) in 2000, with standard deviation 0.56 Mt C resulting from the sources of uncertainty that are considered.     

西部高校怎样更好实现计算机与物理实验的整合

随着计算机的飞速发展,学校里出现了越来越多的多媒体教室;CAI计算机辅助教学、虚拟实验教学等各种软件更是蓬勃发展起来;很多教育工作者提出物理实验中计算机仿真教学、物理实验中应用计算机辅助教学等各种措施.作为西部高校,我们应该根据自身资金有限、学生基础比较薄弱等特点,更好的实现计算机与物理实验的整合.     

An Experimental Evaluation of the Serial Cost Sharing Rule

This paper proposes an experimental test to evaluate the performance of the serial cost sharing rule, originally proposed by Shenker [Sigmetrics, 241–242 (1990)] and then analyzed by Moulin and Shenker [Econometrica 60, 1009–1037 (1992)]. We report measures of the performance and efficiency of the serial mechanism by comparing the choices and payoffs attained by the subjects to the expected equilibrium allocations. Experimental evidence shows that learning is needed for the subjects to converge to the equilibrium strategy. However, in terms of efficiency, the serial mechanism leads to almost efficient allocations.     

基于鲁棒性的关键链二次资源冲突消除策略

以关键链方法中的二次资源冲突困境为切入点,从鲁棒调度优化角度提出一种解决策略.首先,采用定量化建模对问题进行数学描述和表达,剖析插入输入缓冲引起二次资源冲突的原理,进而采用场景分析法从复杂的冲突表象中分解出四种基本的冲突场景构成要素.其次,基于鲁棒调度优化理论,探究各种冲突子问题的有效对策并归类,据此开发出一种消除二次资源冲突的局部重调度启发式协调策略;根据策略设计基于两次调度进程和两类缓冲动态消耗的鲁棒性指标,采用鲁棒性关键链项目调度问题输出鲁棒性最大的调度方案.再次,设计仿真程序和三个测试指标:项目实际按期完工率、活动开始时间偏差绝对值之和及偏差绝对值的方差;基于ProGen随机地生成测试算例集合进行数值实验.结果发现,以鲁棒性调度方案为依据安排项目的实施过程,三个统计指标值都优于以传统关键链调度方案为依据时相对应的指标值.结论表明:基于鲁棒调度优化的二次资源冲突消除策略及设计的关键链鲁棒性指标在项目实施中具有较好的稳定性效果.     

The performance of alternative estimators for the probit model with first-order serial correlation 1

The purpose of the paper is to evaluate the relative performance of two generalized conditional moment (GCM) estimators in terms of their mean squared errors, for the Probit model with first-order serial correlation. The first estimator is a linearized one-step estimator described by Poirier and Ruud (1988). The second one is defined in the present paper. Monte Car10 experiments suggest that the GCM estimators outperform the ordinary Probit estimator. The two GCM estimators do almost equally well, except that the second one may be easier to calculate, especially in large samples.     

Model averaging for treatment effect estimation in subgroups

In many clinical trials, biological, pharmacological, or clinical information is used to define candidate subgroups of patients that might have a differential treatment effect. Once the trial results are available, interest will focus on subgroups with an increased treatment effect. Estimating a treatment effect for these groups, together with an adequate uncertainty statement is challenging, owing to the resulting “random high” / selection bias. In this paper, we will investigate Bayesian model averaging to address this problem. The general motivation for the use of model averaging is to realize that subgroup selection can be viewed as model selection, so that methods to deal with model selection uncertainty, such as model averaging, can be used also in this setting. Simulations are used to evaluate the performance of the proposed approach. We illustrate it on an example early‐phase clinical trial.     

Optimal designs for additive mixture model with heteroscedastic errors

This paper presents a study of D- and A-optimality of direct sum designs for additive mixture models when the errors are heteroscedastic. Sufficient conditions are given so that D- and A-optimal designs for additive mixture models can be constructed from the D- and A-optimal designs for homogeneous models in sub-mixture systems.     

A monte carlo evaluation of response surface analysis based on paired-comparison data

The use of the logit transformation on paired-comparison data in the weighted least squares analysis of response surfaces for aesthetic qualities of products is discussed. Monte Carlo simulations are employed to investigate the small sample properties of the estimators and test statistics. A secondary objective of the Monte Carlo simulations is the comparison of two transformation procedures. The simulations are of standard-item paired-compar-ison experiments in which ties are not allowed.     

Characterization of singular balanced fractional sm factorial designs derivable from balanced arrays with maximum number of constraints

An upper bound on the maximum number of constraints for s-symbol balanced arrays is derived. It is shown that balanced fractional s^m factorial designs derived from some balanced arrays with the maximum possible number of constraints become singular.     

Efficiency of bailey's trigonometric levels in factorial experiments

Bailey has shown that choice of certain trigonometlk levels for factors in a symmetrical confounded factorial design is more efficient for quantitative treatments. This paper introduces certain incidence matrices associated with the flats of different pencils of such designs to obtain an explicit expression for the efficiency and also gives a simpler derivation of Bailey's results.