An alternative estimator for multiple characteristics in PPS sampling

The problem considered relates to large-scale sample surveys. A new estimator of population total for the characteristics that are poorly correlated with the selection probabilities has been developed for the PPSWR sampling scheme. The relative efficiency of the proposed estimator has been studied under a super-population model. A numerical investigation into the performance of the estimator has also been made.     

Estimating powers of the generalized variance under the Pitman closeness criterion

For estimating powers of the generalized variance under a multivariate normal distribution with an unknown mean, the inadmissibility of the closest affine equivariant estimator is shown for the Pitman closeness criterion.     

Minimax-variance L- and R-estimators of location

We consider the problem of minimax-variance, robust estimation of a location parameter, through the use of L- and R-estimators. We derive an easily checked necessary condition for L-estimation to be minimax, and a related sufficient condition for R-estimation to be minimax. Those cases in the literature in which L-estimation is known not to be minimax, and those in which R-estimation is minimax, are derived as consequences of these conditions. New classes of examples are given in each case. As well, we answer a question of Scholz (1974), who showed essentially that the asymptotic variance of an R-estimator never exceeds that of an L-estimator, if both are efficient at the same strongly unimodal distribution. Scholz raised the question of whether or not the assumption of strong unimodality could be dropped. We answer this question in the negative, theoretically and by examples. In the examples, the minimax property fails both for L-estimation and for R-estimation, but the variance of the L-estimator, as the distribution of the observation varies over the given neighbourhood, remains unbounded. That of the R-estimator is unbounded.     

碳强度对中国主要产业部门产值变动敏感性的动态估计

测算产业产值变动对碳强度的作用,可以为碳减排目标下产业结构调整方案的制定提供指导。基于投入产出理论建立系统动力学模型,以此为基础,分析中国主要产业部门产值变动对碳强度的动态作用过程,并从投资结构和消费结构两个方面探讨实现中国主要产业部门碳减排目标的有效途径。研究结果表明:从即期效应来看,制造业,电力、热力及水的生产和供应业,采矿业,其产值增加会使碳强度提高;从动态变化过程来看,农林牧渔业,采矿业,制造业,建筑业,交通运输、仓储和邮电业,批发零售贸易、住宿和餐饮业,房地产、租赁和商务服务业,其产值增加1%后碳强度呈现逐年降低的趋势;从碳强度的变化趋势来看,各产业部门产值增加对碳强度的作用力逐渐趋于稳定;产业产值变动碳减排效力的提高要依靠投资政策。     

脉冲响应函数下的我国货币需求变动与决定

基于V A R模型的脉冲响应函数法和预期方差分解法,分析了我国2000年至2013年期间的货币需求与相关经济因素之间的动态影响特征。研究表明狭义货币、广义货币分别与相关的经济变量存在长期的均衡关系。狭义货币、广义货币对GDP的冲击分别呈现抑制效应、对SV的随机冲击主要呈现正效应、对R的随机冲击主要呈现抑制效应、对CPI的冲击呈现正效应和抑制效应交叉出现的现象。狭义货币、广义货币新息冲击对其自身预测均方误差的贡献度最大。新息冲击对狭义货币预测均方误差的贡献依次为：一年期定期存款名义利率（R）、沪深两市A股总市值（SV）、国内生产总值（GDP）、消费者物价指数（CPI）。新息冲击对广义货币预测均方误差的贡献依次为：国内生产总值（GDP ）、消费者物价指数（CPI ）、一年期定期存款名义利率（R ）、沪深两市A股总市值（S V ）。根据实证结论,得出相关经济变量对货币需求的影响,并据此提出有利于完善货币政策的建议。     

钢铁行业运输环节碳减排情景分析与评价研究

我国钢铁行业碳排放量约为全国碳排放总量的15％,而运输耗能约占物流环节总耗能的5／6。实现钢铁行业中运输环节的节能减排,成为实现我国碳排放总量目标的重要环节。研究钢铁行业中运输环节的碳排放总量与不同碳减排途径及其组合在不同情境下的碳减排潜力,提出基于运输环节碳排放影响因素的碳排放总量测量模型、基于不同减排途径的低碳化分析模型及基于不同途径水平的情景仿真模型。与传统的累计模型不同,低碳化分析模型考虑碳减排途径间的相互影响作用,采用累积形式对减排途径组合进行分析与评价。最终以重庆某钢铁集团20万吨船用钢材作为案例进行情景仿真分析与评价,研究表明：在现有的运输条件下,可通过改变车辆运输方式直接实现0．7到3．9个百分点的碳减排;甩挂运输与混合动力系统改造,可作为优先发展技术,减排效果可达到30％;通过情景仿真分析得知,提高减排途径水平,减排效果将进一步增强。     

The analytic construction of D-optimal designs for the two-variable binary logistic regression model without interaction

Candidate locally D-optimal designs for the binary two-variable logistic model with no interaction, which comprise 3 and 4 support points lying in the first quadrant of the two-dimensional Euclidean space, were introduced by Haines et al. (D-optimal designs for logistic regression in two variables. In: Lopez-Fidalgo J, Rodrigez-Diaz JM, Torsney B, editors. MODA8 – advances in model-oriented designs and analysis. Heidelberg: Physica-Verlag; 2007. p. 91–98). The authors proved algebraically the global D-optimality of the 3-point design for the special case in which the intercept parameter is equal to?1.5434. However for other selected values of the intercept parameter, the global D-optimality of the proposed 3- and 4-point designs was only demonstrated numerically. In this paper, we provide analytical proofs of the D-optimality of these 3- and 4-point designs for all negative and zero intercept parameters of the binary two-variable logistic model with no interaction. The results are extended to the construction of D-optimal designs on a rectangular design space and illustrated by means of two examples of which one is a real example taken from the literature.     

Threshold‐free estimation of functional antibody titers of a group B streptococcus opsonophagocytic killing assay

Opsonophagocytic killing assays (OPKA) are routinely used for the quantification of bactericidal antibodies in blood serum samples. Quantification of the OPKA readout, the titer, provides the basis for the statistical analysis of vaccine clinical trials having functional immune response endpoints. Traditional OPKA titers are defined as the maximum serum dilution yielding a predefined bacterial killing threshold value, and they are estimated by fitting a dose‐response model to the dilution‐killing curve. This paper illustrates a novel definition of titer, the threshold‐free titer, which preserves biological interpretability while not depending on any killing threshold or on a postulated shape of the dose‐response curve. These titers are shown to be more precise than the traditional threshold‐based titers when using simulated and experimental group B streptococcus OPKA experimental data. Also, titer linearity is shown to be not measurable when using threshold‐based titers, whereas it becomes measurable using threshold‐free titers. The biological interpretability and operational characteristics demonstrated here indicate that threshold‐free titers are an appropriate tool for the routine analysis of OPKA data. Copyright © 2015 John Wiley & Sons, Ltd.     

Construction of Simultaneous Confidence Intervals for Ratios of Means of Lognormal Distributions

For constructing simultaneous confidence intervals for ratios of means for lognormal distributions, two approaches using a two-step method of variance estimates recovery are proposed. The first approach proposes fiducial generalized confidence intervals (FGCIs) in the first step followed by the method of variance estimates recovery (MOVER) in the second step (FGCIs–MOVER). The second approach uses MOVER in the first and second steps (MOVER–MOVER). Performance of proposed approaches is compared with simultaneous fiducial generalized confidence intervals (SFGCIs). Monte Carlo simulation is used to evaluate the performance of these approaches in terms of coverage probability, average interval width, and time consumption.