海南人口增长模型的统计分析

介绍了求非线性回归模型参数的基本理论,并且以海南人口增长数据为例,对比_分析了利用Malthus模型和Logistic回归模型的模拟结果.利用Mathematica软件绘制了海南人口增长数据的点图.最后给出海南人口增长数据的拟合曲线和置信域的图形.     

Logistic人口增长模型中资源系数研究

本文研究基于Logistic微分方程的人口增长模型,采用欧拉向前差分法和极限法研究人口增长模型中的极限人口和资源系数的依赖关系,发现当Logistic人口增长模型中参数取特殊情况时系统会出现混沌现象.最后考虑相应的反问题即利用极限人口数来重构资源系数并通过数值算例验证了重构方法的可行性.     

北京市产业结构对经济增长的贡献分析

本文从北京市产业结构的变化情况出发,以1949年-2011年北京市三次产业产值和地区生产总值作为研究对象,首先我们用已有的回归计量经济学模型分析了三个产业对北京市经济增长的贡献,在此基础上提出了变系数回归模型,并将其应用于分析三个产业对北京市经济增长的贡献。应用广义似然比方法检验了回归模型的充分性,并得出三个产业对北京市经济增长的贡献随时间发生显著性变化的结论。最后,结合本文的分析结果,为贯彻落实北京市"十二五"规划,加快产业结构调整和提高产业结构优化程度,我们提出了合理可行的政策建议。     

城镇化进程中洛阳市人口发展的数学建模探讨

针对城镇化进程中洛阳市的人口发展规律,建立了人口发展的一元线性回归模型、指数增长模型以及阻滞增长的Logistic模型来预测洛阳市人口的发展,并与ARIMA模型进行了对比,为城镇化进程中人口发展趋势提供参考,为政策的制定者提供理论指导和决策参考。     

二个四参数增长曲线模型参数初始值的确定方法与模型应用

对非线性回归模型进行非线性最小二乘估计一般需要确定参数初始值.在非线性回归模型中,General Logistic模型和Von Bertalanffy模型是二个含有四参数的增长曲线模型,对数据的拟合有较强的适应性,应用较为广泛.本文给出这两个模型参数初始值的确定方法,并应用于实际拟合,得到很好的效果.     

基于二项分布随机增长的无标度网络

提出—个具有随机增长的无标度网络模型．该模型的演化规则仍然是BA模型的增长和择优连接,但是每一时间间隔添加到网络中的边数是—个具有二项分布的随机变量．通过率方程方法,本文证明了该网络的度分布具有幂律尾部,该模型生成了—个无标度网络．     

一类疾病在食饵中传播的生态-传染病模型分析

分析并建立疾病在食饵中传播的生态-传染病模型,且考虑易感食饵具有常数输入,捕食者种群以Logistic模型增长,讨论了系统解的有界性和各平衡点的存在性,以及局部渐近稳定性,通过构造适当的Lyapunov函数分析了各平衡点的全局渐近稳定性,并运用比较定理证明了系统的持久性.     

一类改进的Logistic模型参数估计方法及其应用

根据实测数据估计Logistic模型参数时,对已有的数据不满足直接利用三点法、四点法应用条件的问题,提出一类改进的三点法、四点法,即迭代逼近算法.以底部耗氧型结冰湖的溶解氧浓度分布为例,建立冰盖下溶解氧浓度垂直分布的Logistic模型,采用迭代逼近算法估计该模型的参数值.结果表明:改进的三点法、四点法的判定系数都较高,均可用于Logistic模型的参数估计,但改进的四点法整体优于改进的三点法.算法进一步完善了Logistic模型的参数估计方法.     

Logistic阻滞增长模型的稳定性与混沌

将Logistic阻滞增长模型的差分形式简化，讨论了它的稳定性，用计算机进行迭代求解。模拟了这一简单差分方程从收敛，分叉，2^n倍周期收敛进入混沌现象的过程。直观地展示了序列{yk}收敛，2倍周期，4倍周期……直至混沌的现象，这对Logistic阻滞增长模型的应用和混沌现象的模拟有很好的参考价值。     

企业退休职工养老金模型

本文讨论了目前我国养老保险体制改革的相关问题。首先,通过分析年工资增长趋势,对其数据进行回归分析,构造出工资的Logistic模型,并预测出职工未来年份的年平均年工资;其次构造养老金替代率模型,并得到多种情况下的替代率;再次,建立养老金缺口模型,用来分析养老金缺口情况以及达到平衡时领取养老金的年数;最后分析得出影响养老金替代率和收支平衡的4个因素,即社会统筹基金的缴费比例、基金收益率、退休年龄和开始缴纳养老保险的年龄,对其进行敏感性分析,并提出一些相应的改进建议。     

Effects of power law logistic technologies on economic growth

Based on the S-shaped power law logistic technology, we set up an economic growth model in this paper. The solution of the model is given via hypergeometric functions. We show that the dynamics of the model is asymptotically stable. And, it is found that the dynamics of the model is actually controlled by the power law logistic function through an ordinary logistic function, as a power function of the power law logistic. From the statistical point of view, in this paper, three different types of power law index means three different types of skewness, giving three different types of growth and diffusion patterns of technology. Then, we show some comparison results of different types of technology and of different initial levels of capital, and their effects on economic growth. A numerical example is also given in this paper to illustrate the effects.     

L1正则化Logistic回归在财务预警中的应用

线性模型和广义线性模型已广泛地用于社会经济、生产实践和科学研究中的数据分析和数据挖掘等领域,如公司财务预警,引入L1范数惩罚技术的模型在估计模型系数的同时能实现变量选择的功能,本文将L1范数正则化Logistic回归模型用于上市公司财务危机预报,结合沪深股市制造业ST公司和正常公司的T-2年财务数据开展实证研究,舛比Logistic回归和L2正则化Logistic回归模型进行对比分析.实验结果表明L1正则化Logistic回归模型的有效性,其在保证模型预测精度的同时提高模型的解释性.     

MODELING INDIVIDUAL TREE MORTALITY RATES USING MARGINAL AND RANDOM EFFECTS REGRESSION MODELS

Abstract Developing models to predict tree mortality using data from long‐term repeated measurement data sets can be difficult and challenging due to the nature of mortality as well as the effects of dependence on observations. Marginal (population‐averaged) generalized estimating equations (GEE) and random effects (subject‐specific) models offer two possible ways to overcome these effects. For this study, standard logistic, marginal logistic based on the GEE approach, and random logistic regression models were fitted and compared. In addition, four model evaluation statistics were calculated by means of K‐fold cross‐valuation. They include the mean prediction error, the mean absolute prediction error, the variance of prediction error, and the mean square error. Results from this study suggest that the random effects model produced the smallest evaluation statistics among the three models. Although marginal logistic regression accommodated for correlations between observations, it did not provide noticeable improvements of model performance compared to the standard logistic regression model that assumed impendence. This study indicates that the random effects model was able to increase the overall accuracy of mortality modeling. Moreover, it was able to ascertain correlation derived from the hierarchal data structure as well as serial correlation generated through repeated measurements.     

应急物流能力突变模型研究

运用燕尾突变理论,以物流能力为状态变量,物流流量变化率、流速变化率和时间变化率为控制变量,建立应急物流能力突变模型,运用势函数确定了分岐点集,讨论了应急物流能力的突变临界点及稳定性,并用算例分析模型应用的可行性.最后得出三点结论:根据实测及调查数据可以确定三个控制变量的值,从而确定控制点在分歧点集的区域;通过计算分析可以确定应急物流能力在分岐点集各区域的奇点个数和性质;其突变方向和可能性随之可以确定:控制点从奇点多的区域向奇点少的区域移动,应急物流能力发生突变的可能性大,反之可能性小,甚至不发生突变.因此把握控制点在分岐点集中的变化方向和规律,采取相应措施改变相应控制变量,可以提升或稳定应急物流能力.     

Long term behaviors of stochastic single-species growth models in a polluted environment

Thresholds for extinction and persistence are important for assessing the risk of mortality in systems exposed to toxicant. In this paper, three single-species models with random perturbation in a polluted environment are proposed and investigated. One is the generalized logistic model and the other two are the stochastic resource–consumer models of Leslie and Gallopin. For each model, the survival threshold is obtained in some cases. In general, each threshold is determined by intensity of the random noise, the mean stress measure in organisms, the population intrinsic growth rate and the stress response rate.     

Comparison of time risks based on a multinomial logistic response model in longitudinal studies

Summary The multinomial logistic response model has been used in the analysis of data from longitudinal studies of RERF's mortality cohort population. The model was restricted to linear and quadratic doseresponses for practical as well as biological reasons. The advantages and disadvantages of the multinomial logistic model are pointed out. Numerical comparison is made of the maximum likelihood (ML) estimates of parameters obtained by binomial and multinomial logistic procedures. The dose-response difference between two independent “same age” groups is evaluated from the ML estimates of parameters under a linear logistic response model. A significant dose-response difference between two independent “same age” groups in the years 1950–1959 and 1960–1969 is noted only for the 15–24 age group for all cancers other than leukemia. Radiation Effects Research Foundation     

Logistic evolutionary product-unit neural networks: Innovation capacity of poor Guatemalan households

A new logistic regression algorithm based on evolutionary product-unit (PU) neural networks is used in this paper to determine the assets that influence the decision of poor households with respect to the cultivation of non-traditional crops (NTC) in the Guatemalan Highlands. In order to evaluate high-order covariate interactions, PUs were considered to be independent variables in product-unit neural networks (PUNN) analysing two different models either including the initial covariates (logistic regression by the product-unit and initial covariate model) or not (logistic regression by the product-unit model). Our results were compared with those obtained using a standard logistic regression model and allow us to interpret the most relevant household assets and their complex interactions when adopting NTC, in order to aid in the design of rural policies.     

"物流配送中心选址的随机数学模型"的有效性研究

从实际应用出发，对文献[1]中提出物流配送中心选址的随机数学模型进行了有效性分析。通过计算机模拟得到的数据，分别应用随机数学模型和传统选址方法对不同规模的配送网络进行选址，通过分析两者在不同条件下的总费用，得到了该随机模型的一些有趣的性质，为实际中的应用提供了依据。     

Tractors in Spain: A Logistic Analysis

This paper presents an attempt to make reliable projections of the stock of agricultural tractors in Spain. The approach to be followed is that of fitting a logistic trend to the historical data for the period 1951-1976. A set of possible trend curves is presented and their properties discussed; reasons for choosing the logistic trend are given. Preliminary estimates for the parameters of the logistic are obtained by means of the relatively unsophisticated three point method. Alternative heteroscedasticity assumptions in the data are explored with the help of a non-linear regression. Final estimates are obtained by means of a non-linear optimization algorithm. The influence of economic variables and government policies is traced in the residuals.     

Modeling company failure: a longitudinal study of Turkish banks

Determining the factors related to the financial failure of a company is important. In this paper, we extend literature on bank failure prediction by modelling bank failures in Turkey from 1998 to 2000 using three statistical models combined with a principal component analysis on financial ratios. The three statistical models employed are a logistic regression, a logistic regression that takes serial correlation into account via generalized estimating equations and a marginalized transition model (MTM). Time and financial ratios that are related with capital adequacy and profitability, risk, non-interest income and Fx assets to Fx liabilities are found to be significant in classifying failed banks. Each of our methods achieves a correct classification rate of 93.3%. Among the three models, MTM, which is the soundest model in terms of statistical assumptions, shows slightly better model fit properties.