基于GM(1,1)与主成分回归的海南GDP预测及其影响因素分析

以海南省年度GDP为衡量经济增长指标变量,以旅游业总收入、农林牧渔业增加值、建筑业增加值、固定资产投资总额、社会消费品零售总额及对外贸易进出口总额六个指标作为影响因素,采用多个标准对1987-2014年数据进行筛选,建立GM(1,1)模型对海南GDP及其影响因素进行5年预测,来分析海南经济结构变动趋势.利用灰色关联分析定性分析了六个行业对GDP的影响程度;从定量分析角度,利用线性主成分回归模型和对数主成分回归模型分别对海南GDP进行边际、弹性分析.发挥了灰色系统科学理论和计量经济模型各自长处,为建设海南国际旅游岛相关政策的制定提供参考.     

人口增长率的非参数自回归预测模型

针对传统的人口增长预测模型不能理想地捕获我国人口增长率数据的非线性性特征,本文基于局部线性非参数估计理论,对我国建国以来的年人口增长率建立了非参数自回归NAR(1)模型,并对2000-2003年的年人口增长率进行了预测,计算结果表明,相对于参数自回归模型而言,非参数自回归模型能够很好地解决人口增长预测这一非线性问题,预测精度较高。     

中国人口增长的脉冲突变与趋势预测

利用中国统计年鉴中1949-2016年有关中国人口的数据,研究了全面二孩政策对中国人口产生的一个脉冲突变,建立了具有脉冲的Richards人口增长模型,并且利用数值模拟方法研究2016年中国人口增长的脉冲突变,并且预测了中国人口的发展趋势和中国人口的峰值.     

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。     

基于RVM模型的国内游客流量预测研究——以海南为例

引入RVM对海南旅游景区接待国内游客流量进行预测,并利用2011年1月至2016年12月海南交通行业数据和相应的网络搜索数据构建模型的输入集.12个月的预测结果表明,与基准模型相比,RVM具有更优异的预测性能,证实了模型在旅游需求预测领域的有效性.     

基于动力学模型的人口数量预测和政策评估

随着单独二胎政策的放开,计划生育政策再次引起了人们的关注.为评估生育胎次对中国人口数量的影响,本文建立了关于人口增长的动力学模型.首先,分别对辽宁省和新疆自治区的人口数据进行了拟合,评估了"二胎"政策对两地区人口的影响.其次,对全国人口数据和抚养比进行了拟合和预测.最后,通过参数敏感性分析,评估各因素对总人口增长的影响.     

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.     

基于GWR模型的河南省人口分布的影响因素研究

近年来,人口作为一种基本信息已成为目前研究的热点问题之一.人口分布可能受自然,经济,社会,政治等诸多因素的影响.因此,人口分布的研究对于了解不同类型区域的人口资源与经济发展之间的关系,因地制宜地发展本地经济具有重大意义.课题以河南省统计年鉴数据为基础,研究河南省人口分布的影响因素.具体来说,首先利用Surfer软件的可视化技术研究了河南省人口数量的空间变化特征.其次,利用近年来发展起来的地理加权回归模型对河南省人口分布的影响因素进行了定量分析.通过上述分析提取有效信息,从而为制定合理的人口政策和实现人口的有序流动提供必要的理论支持.     

具有人口年龄结构的Solow-Swan模型与仿真

本文中,我们将人口年龄结构引入经典的Solow-Swan模型,探讨人口年龄结构变动对经济增长的影响.利用比较定理证明当人口趋于稳定的人口结构时刻划模型的微分方程的解是渐近稳定的.通过数值仿真,我们看到经济增长在少年抚养下降时加速,在老年抚养上升时减缓.在人口转变时期存在"人口红利",人口老龄化导致的劳动力人数占人口的比重下降会使经济增长减缓甚至下降.     

部分函数型线性空间自回归模型的假设检验

本文提出了部分函数型线性空间自回归模型的空间效应以及参数效应的假设检验问题.首先利用函数型主成分分析方法估计斜率函数,利用广义矩估计方法估计参数.然后利用得到的相合估计,在原假设和备择假设下,构造了基于残差平方和的检验统计量,同时给出了此检验统计量的渐近性质.模拟结果表明在有限样本下,检验统计量具有良好表现.最后将部分函数型线性空间自回归模型的检验应用到一个关于经济增长的数据案例中,说明所提出的检验统计量的应用表现.     

基于ARIMA模型对海南省社会消费品零售总额的预测

对海南省社会消费品零售总额进行预测,对于了解海南省社会消费品零售总额的发展态势,为有关部门作出决策提供科学的依据,具有重大的现实经济意义.选取1999年到2014年的海南省社会消费品零售总额的数据来建立ARIMA(1,3,2)模型,2012年到2014年的实际值与预测值的相对误差5%以内,拟合效果良好,说明采用ARIMA模型预测海南省社会消费品零售总额是可行的,预测数据可靠.最后对海南省2015-2018年的社会消费品零售总额进行预测.     

Interpolation solution in generalized stochastic exponential population growth model

In this paper, first we consider model of exponential population growth, then we assume that the growth rate at time t is not completely definite and it depends on some random environment effects. For this case the stochastic exponential population growth model is introduced. Also we assume that the growth rate at time t depends on many different random environment effect, for this case the generalized stochastic exponential population growth model is introduced. The expectations and variances of solutions are obtained. For a case study, we consider the population growth of Iran and obtain the output of models for this data and predict the population individuals in each year.     

中国人口增长与粮食生产的协整研究

本文以1978-2004年为样本数据,对中国人口和粮食产量进行了单位根检验、协整检验和Granger因果关系检验.结果表明,样本期内人口因素不是粮食生产的Geanger原因,人口增长和粮食生产发展并不协调.通过建立中国粮食生产模型,预测了2006-2010年的人口增长与粮食生产趋势,提出了实现中国人口增长与粮食生产和谐发展的几点建议.     

ESTIMATING A STOCHASTIC MODEL OF POPULATION DYNAMICS WITH AN APPLICATION TO KANGAROOS

In this study, we derive stochastic models of population dynamics and devise a new method of estimating the models. The models allow growth and harvest to be nonlinear functions of stochastic processes and the error terms to be nonlinear and heteroskedastic. Ordinary least-squares estimates would be biased and inefficient and generalized least-squares estimates cannot be calculated. Therefore, we implement nonlinear maximum likelihood methods to find unbiased and efficient estimates of parameters. The method is applied to the population dynamics of kangaroos in South Australia. Aerial survey data of kangaroo numbers are combined with harvest, effort and rainfall data to estimate the growth and harvest functions and the variances of the stochastic processes which drive the system. Results suggest that growth and harvest should be modeled as functions of stochastic processes and that observations on kangaroo numbers are critical for estimating population dynamics. The results also indicate that the estimation method works well and is a viable alternative to ARIMA and GARCH models, particularly for small data sets.     

POSSIBILITIES AND LIMITATIONS OF USING HISTORIC PROVENANCE TESTS TO INFER FOREST SPECIES GROWTH RESPONSES TO CLIMATE CHANGE

Abstract. Under projected changes in global climate, the growth and survival of existing forests will depend on their ability to adjust physiologically in response to environmental change. Quantifying their capacity to adjust and whether the response is species‐ or population‐specific is important to guide forest management strategies. New analyses of historic provenance tests data are yielding relevant insights about these responses. Yet, differences between the objectives used to design the experiments and current objectives impose limitations to what can be learned from them. Our objectives are (i) to discuss the possibilities and limitations of using such data to quantify growth responses to changes in climate and (ii) to present a modeling approach that creates a species‐ and population‐specific model. We illustrate the modeling approach for Larix occidentalis Nutt. We conclude that the reanalysis of historic provenance tests data can lead to the identification of species that have population‐specific growth responses to changes in climate, provide estimates of optimum transfer distance for populations and species, and provide estimates of growth changes under different climate change scenarios. Using mixed‐effects modeling techniques is a sound statistical approach to overcome some of the limitations of the data.     

Measure-valued solutions for a hierarchically size-structured population

We present a hierarchically size-structured population model with growth, mortality and reproduction rates which depend on a function of the population density (environment). We present an example to show that if the growth rate is not always a decreasing function of the environment (e.g., a growth which exhibits the Allee effect) the emergence of a singular solution which contains a Dirac delta mass component is possible, even if the vital rates of the individual and the initial data are smooth functions. Therefore, we study the existence of measure-valued solutions. Our approach is based on the vanishing viscosity method.     

A FULL ANNUAL CYCLE MODELING FRAMEWORK FOR AMERICAN BLACK DUCKS

American black ducks (Anas rubripes) are a harvested, international migratory waterfowl species in eastern North America. Despite an extended period of restrictive harvest regulations, the black duck population is still below the population goal identified in the North American Waterfowl Management Plan (NAWMP). It has been hypothesized that density‐dependent factors restrict population growth in the black duck population and that habitat management (increases, improvements, etc.) may be a key component of growing black duck populations and reaching the prescribed NAWMP population goal. Using banding data from 1951 to 2011 and breeding population survey data from 1990 to 2014, we developed a full annual cycle population model for the American black duck. This model uses the seven management units as set by the Black Duck Joint Venture, allows movement into and out of each unit during each season, and models survival and fecundity for each region separately. We compare model population trajectories with observed population data and abundance estimates from the breeding season counts to show the accuracy of this full annual cycle model. With this model, we then show how to simulate the effects of habitat management on the continental black duck population.     

中国人口老龄化对经济增长的影响研究

在全球老龄化趋势的大背景下,探究人口老龄化问题对经济增长的影响,已经成为学界研究的一个热点.依据中国国家统计局发布的统计数据,采用定性分析与定量分析相结合的方法,分析了各省(市)的老龄化状况以及通过回归模型定性分析老龄人口抚养比对GDP增长的影响.针对目前人口老龄化对中国经济增长产生的不良影响,提出了在我国目前经济还不发达的情况下应加快科技发展,提高生产效率,合理开发老年人才资源等方法,以促进我国的经济增长保持良好的态势.     

Survival criterion for a population subject to selection and mutations; Application to temporally piecewise constant environments

We study a parabolic Lotka–Volterra type equation that describes the evolution of a population structured by a phenotypic trait, under the effects of mutations and competition for resources modelled by a nonlocal feedback. The limit of small mutations is characterized by a Hamilton–Jacobi equation with constraint that describes the concentration of the population on some traits. This result was already established in Barles and Perthame (2008); Barles et al. (2009); Lorz et al. (2011) in a time-homogeneous environment, when the asymptotic persistence of the population was ensured by assumptions on either the growth rate or the initial data. Here, we relax these assumptions to extend the study to situations where the population may go extinct at the limit. For that purpose, we provide conditions on the initial data for the asymptotic fate of the population. Finally, we show how this study for a time-homogeneous environment allows to consider temporally piecewise constant environments.     

Does movement toward better environments always benefit a population?

We study the effects of advection along environmental gradients on logistic reaction-diffusion models for population growth. The local population growth rate is assumed to be spatially inhomogeneous, and the advection is taken to be a multiple of the gradient of the local population growth rate. It is also assumed that the boundary acts as a reflecting barrier to the population. We show that the effects of such advection depend crucially on the shape of the habitat of the population: if the habitat is convex, the movement in the direction of the gradient of the growth rate is always beneficial to the population, while such advection could be harmful for certain non-convex habitats.