利用C_p准则筛选影响猪胴体瘦肉量的最优子集

本文把猪胴体瘦肉量作为因变量，胴体重、眼肌面积、胴体长、背膘厚和屠宰日龄作为自变量，组成了31个可能产生的自变量子集，利用C_p准则分析了变量及组合在不同子集中的作用，筛选出了以胴体重、眼肌面积、胴体长、和背膘厚组成的最优子集．     

谈立体几门课本中一道例题的多功能使用

谈立体几门课本中一道例题的多功能使用７２６０００陕西省商州中学党效文课本中有些例题，看似很平常、一般．如果在教学中只作一般牲的讲解，使例题的深度、广度不能集中表现出来，这就很难引起学生的重视，也就没有起到例题应有的典型示范作用，那么怎样才能提高课本例...     

广西地区经济指标评价

杨善朝，李志友．广西地区经济指标评价．数理统计与管理，１９９７，１６，（４），１～４本文试用主成分分析方法，对广西七个地区的经济生产情况作出综合评价，分析各地区在广西的经济地位。并提出了一种构造加权综合量的方法     

混合线性模型效应参数的影响分析

该文考虑非平衡混合线性模型的影响分析及强影响点的探测问题．文中导出了在单点剔除模型下效应参数的经验Ｂａｙｅｓ估计与原模型下对应估计的相互关系．利用Ｃｏｏｋ距离和协方差比统计量，我们分别给出了剔除单个数据点对固定效应和随机效应参数估计以及估计精度的影响度量．最后，给出具体的计算方法，并对一实例进行分析．     

生猪生产的最优利润

线性规划（ＬＰ）用于确定饲料最低费用配比已有多年的历史。但确定饲料配比仅是农场主所关心的一件事，他们的主要目的是为了从生产中获取最大的利润。本文提出了基于ＬＰ的饲料规划方案，以便使猪是佳地生长，同时也使养猪者获取更大的生产利润。在最大利润模型中，售价和重量的乘积作为收入，饲料费和间接费作为成本。解中包括猪饲料的总量和猪应有的最佳重量。为了把猪的生长模式引入到ＬＰ模型中，我们用数学生长函数来表达生长率和猪龄之间的关系。该函数是经过适当的转化，用回归方法估算出来的。猪在不同生长阶段的营养需求是依据其生长模型和饲料转化率分析的。把上述结果全都引用到ＬＰ模型中，这样可以使利润最优化。实际数据的检验表明：在实践中，ＬＰ模型的结果是合理的。     

考试目标和命题原则（续完）

考试目标和命题原则（续完）晨旭（接上期）门）控制试卷长度、卷面字数和计算量．试卷长度直接反映了试卷中题目数量，对实现考试目标有一定影响．题量过少，将不能全面考查各种知识、方法和能力，而且在客观上会助长猜题押题的风气；题量过大，多数考生在规定时间内不能...     

可拆分平行机排序问题研究

平行机排序问题是把n个产品安排到m台机器上加工，使其总费用最小．通常的平行机排序问题都假设（C1）：任何产品不能在不同机器上同时加工．但是，如果把产品的加工时间看成一个产品量的需求，就可以假设（C2）：允许同一产品拆分在不同机器上同时加工．本文首先回顾了C1假设下平行机排序问题已有的结果，然后基于假设C2，讨论了各种费用目标下问题的算法及其复杂性．在没有生产准备时间的情况下，给出了一些问题的多项式算法和线性规划方法．在有独立生产准备时间的情况下，给出了P／split／Cmax问题的启发式算法及其算法分析．     

层次分析法在湖南省粮食生产发展对策分析中的应用

本文综述了层次分析法的基本原理和过程，建立了湖南省粮食生产发展对策分析的层次分析模型，对影响湖南省粮食生产发展的多种因素进行了综合排序，其结果有一定的实际指导意义．     

在非线性回归模型中误差为AR(2)的相关性检验

本文讨论了在非线性回归模型中误差为AR(2)的相关性检验，得到了误差相关性检验的似然比检验统计量、Score检验统计量．对感兴趣参数和多余参数，利用Cox and Reid(1987)提出的正交化方法，给出了修正的似然比检验统计量和Score检验统计量．推广了胡跃清，韦博成(1994)讨论的在非线性回归模型中误差为AR(1)相关性检验的结果．     

具有测量误差的非线性模型的Bayes估计

测量中大量的函数模型都是非线性回归模型．当回归变量含有一定的测量误差时，我们得到非线性测量误差模型．本讨论了这种模型中未知参数具有正态先验分布时的参数Bayes估计方法，并对这种估计进行了影响分析，证明了删除模型与均值漂移模型中参数的Bayes估计相同，利用Cook统计量给出了删除模型下参数的Bayes估计的影响度量．     

A Dynamic Programming Model for Pig Production

The feeding policy of a pig production unit affects both the cost of production and the weight and carcase composition of the pigs produced. Since the market value of the pigs produced is determined by the weight and composition of the carcase, feeding policy has a major influence on the economic performance of the unit. In order to evaluate possible feeding policies, the effect of feed intake on both the weight and the body composition of the growing pig must be known, and since an optimal policy will involve using least cost rations, it must be possible to determine the least cost rations to produce liveweight gains of specified body composition. A dynamic programming model to determine the optimal feeding policy to produce pigs of specified weight and carcase composition is developed using a published pig growth model which allows the formulation of the required least cost rations, and the use of this dynamic programming model is illustrated.     

湖南省武陵山片区旅游收入与农民增收的关联研究——基于四个市（州）数据的实证分析

结合湖南省武陵山片区实际,以邵阳市、张家界市、湘西土家族苗族自治州和怀化市为研究对象,对其旅游收入与农民增收的关联情况进行分析.研究发现,旅游总收入与第一产业增加值和农民人均纯收入之间均存在显著的相关性.旅游总收入对第一产业增加值和农民人均纯收入的提升具有重要促进作用.     

农业现代化视阈下基于SPSS多元回归分析的全国农业总产值主要影响因素探究

随着我国城镇化的快速发展,大批农业劳动力向城市转移,农业总产值及其主要影响因素的研究已经成为热点问题.为研究我国农业总产值的主要影响因素,本文借助多元回归分析的相关理论抽取了2016年我国农业投入的31个省市的相关截面数据,采用最小二乘法,利用SPSS软件进行多元回归分析,得到回归模型,并基于该模型找出我国农业总产值的主要影响因素.     

基于动态财务分析的地质灾害保险定价

将经济学中的动态财务分析(DFA)模型应用于地质灾害保险定价中,对离散的灾害事件、经济损失等进行建模分析,计算出纯保费.实证分析以湖南省邵阳市为例,结果表明该模型实用性强、操作简单,计算出来的保费率具有一定的参考价值.     

Supply chain optimization of petroleum organization under uncertainty in market demands and prices

A multi-period stochastic planning model has been developed and implemented for a supply chain network of a petroleum organization operating in an oil producing country under uncertain market conditions. The proposed supply chain network consists of all activities related to crude oil production, processing and distribution. Uncertainties were introduced in market demands and prices. A deterministic optimization model was first developed and tested. The impact of uncertainty on the supply chain was studied by performing a sensitivity analysis in which ±20% deviations were introduced in market demands and prices of different commodities. A stochastic formulation was then proposed, which is based on the two-stage problem with finite number of realizations. The proposed stochastic programming approach proved to be quite effective in developing resilient production plans in light of high degree of uncertainty in market conditions. The anticipated production plans have a considerably lower expected value of perfect information (EVPI). The main conclusion of this study is that for an oil producing country with oil processing capabilities, the impact of economic uncertainties may be tolerated by an appropriate balance between crude exports and processing capacities.     

Optimizing pig marketing decisions under price fluctuations

In the manufacturing of fattening pigs, pig marketing refers to a sequence of culling decisions until the production unit is empty. The profit of a production unit is highly dependent on the price of pork, the cost of feeding and the cost of buying piglets. Price fluctuations in the market consequently influence the profit, and the optimal marketing decisions may change under different price conditions. Most studies have considered pig marketing under constant price conditions. However, because price fluctuations have an influence on profit and optimal marketing decisions it is relevant to consider pig marketing under price fluctuations. In this paper we formulate a hierarchical Markov decision process with two levels which model sequential marketing decisions under price fluctuations in a pig pen. The state of the system is based on information about pork, piglet and feed prices. Moreover, the information is updated using a Bayesian approach and embedded into the hierarchical Markov decision process. The optimal policy is analyzed under different patterns of price fluctuations. We also assess the value of including price information into the model.

     

A spreadsheet-based optimization model for the integrated problem of producing and distributing a major weekly newsmagazine

In this paper, we address the problem of producing and distributing the Brazilian newsmagazine Época, a major weekly publication with one of the 10 largest circulations in the world. This real-world problem had been puzzling magazine publishers in Brazil and remained unsolved for many years. We propose an innovative mixed-integer-linear programming model to determine the number and location of the industrial facilities that should produce the magazines, what destinations should be assigned to each selected facility; the production sequencing and the modes of transportation (air or truck). Our model aims to minimize the total cost while adhering to production capacity and time constraints. The model was implemented in an electronic spreadsheet environment and yielded a savings of 7.1% of the total costs. Given that despite their huge popularity, little has been written on the issues of implementing full-scale optimization models in spreadsheets; thus we also provide the details of the model’s implementation in Excel.     

Comparing frontier methods for economic–environmental trade-off analysis

This paper uses a mechanistic frontier approach as a reference to evaluate the ability of conventional parametric (SFA) and non-parametric (DEA) frontier approaches for analyzing economic–environmental trade-offs. Conventional frontier approaches are environmentally adjusted through incorporating the materials balance principle. The analysis is worked out for the Flemish pig finishing case, which is both representative and didactic. Results show that, on average, SFA and DEA yield adequate economic–environmental trade-offs. Both methods are good estimators for technical efficiency. Cost allocative and environmental allocative efficiency scores are less robust, due to the well-known methodological advantages and disadvantages of SFA and DEA. For particular firms, SFA, DEA and the mechanistic approach may yield different economic–environmental trade-offs. One has therefore to be careful when using conventional frontier approaches for firm-specific decision support. The mechanistic approach allows for optimizing performances per average present finisher, which is the production unit in pig finishing. Conventional frontier methods do not allow for this optimization since the number of average present finishers varies along the production functions. Since the mechanistic production function is based on underlying growth, feed uptake and mortality functions, additional firm-specific indicators can also be calculated at each point of the production function.