中国火电企业生产效率评价与影响因素研究

基于2008~2017年省级统计数据,研究中国火电企业生产效率与影响因素.首先,运用Bootstrap方法修正的DEA模型研究火电企业静态效率;其次,结合全局参比Malmquist指数的可传递性研究火电企业动态效率;最后,运用Tobit模型研究火电企业生产效率影响因素,基于稳健性考虑运用固定效应模型验证检验结果的可靠性.效率评价实证结果显示：2008~2017年无一省（自治区、直辖市）的火电企业生产效率处于生产前沿面,也无一省（自治区、直辖市）的火电企业生产效率持续提高.2008~2013年全国火电企业生产效率比较平稳,2013~2016年呈下降趋势且省际差异逐步扩大,2017年有所回升.2008~2017年东中西三大地带火电企业效率和平稳性呈现东部最优、中部次之、西部最差的格局.影响因素实证结果显示：设备性能、经济发展速度、市场竞争程度是火电企业生产效率的显著影响因素;政府对环境污染重视程度和碳排放权交易市场对火电企业生产效率影响有限.     

A weight-adjusted Peto’s test when cause of death is not assigned

A new statistical testing approach using a weighted logrank statistic is developed for rodent tumorigenicity assays that have a single terminal sacrifice but not cause-of-death data. Instead of using cause-of-death assignment by pathologists, the number of fatal tumors is estimated by a constrained nonparametric maximum likelihood estimation method. For data lacking cause-of-death information, the Peto test is modified with estimated numbers of fatal tumors and a Fleming–Harrington-type weight, which is based on an estimated tumor survival function. A bootstrap resampling method is used to estimate the weight function. The proposed testing method with the weight adjustment appears to improve the performance in various situations of single-sacrifice animal experiments. A Monte Carlo simulation study for the proposed test is conducted to assess size and power of the test. This testing approach is illustrated using a real data set.     

直升机旋翼动平衡振动信号的等角度重采样算法研究

目的 准确测量直升机旋翼基频振动的强度和相位,开展对基于振动信号降噪的等角度采样算法研究。方法 基于直升机旋翼动平衡检测的经典架构,提取桨毂传导过来的啮齿咬合振动信号,作为等相位采样的标尺,从而将振动数据从等时间采样,转换为等角度采样,减少转速微弱波动导致的相位非均匀采样对快速傅里叶变换的影响。结果 针对某型现役直升机在满速下获得的主旋翼测试数据,在经过上述方法进行重采样后,测量结果的滚动平均振动强度和相位的波动性明显降低,振动波动小于±0.01IPS,相位波动小于±10°。结论 在采用加速度传感器的条件下,通过采用啮齿咬合高频信号作为标尺,对振动信号进行等角度重采样可以提高测量的精确度。     

基于信息扩散与自助法的旱灾风险评估模型──以安徽为例

旱灾风险管理是抗旱减灾的科学手段、干旱及旱灾研究的重要方向,定量评估旱灾风险是旱灾风险管理的核心内容。为降低各种不确定性因素影响下旱灾风险评估结果的误差,提高结果的可靠性,提出运用信息扩散法估计旱灾损失的超越概率,结合自助法的区间估计算法,建立基于信息扩散与自助法的灾害风险评估模型,用不同置信水平下旱灾损失对应超越概率的置信区间来反映旱灾风险。将该模型运用于安徽省农业易旱地区干旱灾害风险评估,计算并确定在置信水平为0.75时安徽省易旱地区的旱灾风险区间评估结果合理、可靠,可为抗旱规划提供科学的决策依据。     

Non-parametric MLE for Poisson species abundance models allowing for heterogeneity between species

The proper management of an ecological population is greatly aided by solid information about its species' abundances. For the general heterogeneous Poisson species abundance setting, we develop the non-parametric mle for the entire probability model, namely for the total number N of species and the generating distribution F for the expected values of the species' abundances. Solid estimation of the entire probability model allows us to develop generator-based measures of ecological diversity and evenness which have inferences over similar regions. Also, our methods produce a solid goodness-of-fit test for our model as well as a likelihood ratio test to examine if there is heterogeneity in the expected values of the species' abundances. These estimates and tests are examined, in detail, in the paper. In particular, we apply our methods to important data from the National Breeding Bird Survey and discuss how our methods can also be easily applied to sweep net sampling data. To further examine our methods, we provide simulations for several illustrative situations.     

Comparisons between air-transport models via bootstrapped significance tests

The bootstrap resampling method is used to help with the intercomparison of air transport models. Time-by-time analysis of variance and follow up simultaneous comparisons are proposed which do not rely on distributional assumptions for the predictions of the models and which allow errors to be postulated in the observed values of the phenomena under investigation. The techniques are demonstrated using some data from the APSIS experiment.     

A model of deforestation by human population interactions

A differential equation was employed in modelling deforestation by human population interactions to yield an explicit mathematical model. The theoretical relation and many possible models were applied to the grid cell data in Hiroshima Prefecture, and relative appropriateness of each model was evaluated by Akaike's information criterion (AIC) using raw data. Intensive further verification was executed bythe bootstrap method. It was demonstrated that the theoretical relation was in the best agreement among many other models in comparison.     

LONG TERM TRENDS OF ANNUAL AND MONTHLY PRECIPITATION IN JAPAN1

ABSTRACT: Long term trends in Japan's annual and monthly precipitation are investigated in this study. The statistical significance of a trend at a study site is assessed by the Mann‐Kendall (MK) test, and field significance of trends in climatic Regions II, III, and IV is evaluated using the bootstrap test preserving cross correlation. The practical significance of a trend is judged by a percentage change of the sample mean over an observation period. The field significance assessment demonstrates that annual precipitation in Region II did not show any significant change, but regional precipitation shifts occurred in different months. Precipitation significantly increased by 12.2 percent in May, while it significantly decreased by 12.0, 10.5, 15.6, and 19.7 percent, respectively, in April, September, October, and December. In Region III, annual precipitation declined by 11.8 percent, and monthly precipitation significantly decreased from September through January and in April, with the greatest decrease (38.2 percent) in December. In Region IV, significant reductions occurred in both annual precipitation (by 15.6 percent) and monthly precipitation from September through February and in June and July, with the worst reduction (44.7 percent) in December.     

最近邻抽样回归模型在水环境预测中的应用

介绍了最近邻抽样回归模型(NNBR)进行单因子和多因子预测建模的基本思想和算法.该模型概念清晰,结构简单,不需对研究对象的相依形式和概率分布形式作假定,也不需估计太多的参数,是一类数据驱动的非参数预测模型,具有潜在的优势.通过水环境中的两个实例进行了预测应用,结果表明,预测效果较好,并与投影寻踪回归模型(PPR)进行了对比.