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1.
以非可加模糊测度代替经典可加测度,基于模糊积分建立非线性回归模型是新近出现的数据建模方法.该方法充分考虑自变量因素之间的信息熔合(含协同或冲突)作用.本文完整地给出了适用于实数范围内的基于模糊积分(含Choquet积分和(S)ipo(s)积分)的多元非线性回归模型转化为普通线性回归模型的非线性转换方法及其简化算法.并将该方法应用于金融市场数据分析,结果表明效果较之普通多元线性回归有大的提高,且方法简便容易应用.  相似文献   

2.
介绍了甘肃省物流业的实际状况,其次建立了甘肃省经济发展和甘肃省物流业发展的二级评价指标体系,运用基于方差加权法与熵值法相结合的综合赋权法的非线性评价模型分别对甘肃省经济发展的综合实力和物流业发展的综合实力进行评价.最后基于回归和隶属度函数相结合的方法,运用物流业和经济发展的综合实力评价结果分析计算甘肃省物流系统与经济系统的协调测度,根据计算的测度绘制散点图,对甘肃省物流系统与经济系统的协调度进行分析评价.  相似文献   

3.
以1993-2007年数据为根据,采用逐步回归方法,建立中国城镇居民消费支出的多元非线性回归模型.结果表明:影响居民消费支出的主要因素有收入、消费意愿、居住面积、商品零售价格.消费支出随着收入、消费意愿、商品零售价格的提高而提高,随着人均居住面积的增加而先增后减.而且多元非线性回归模型比线性回归模型更能准确描述客观实际结果.  相似文献   

4.
在网络供需都不确定的情况下,提出一个考虑路段关联的路径选择模型.假定网络中每一用户的路径选择效用受到三个因素的影响:出行时间均值、出行成本均值和以出行时间方差表现的出行时间可靠性.在出行路径选择效用最大化前提下,修改了出行阻抗单调可分的常见假设,考虑出行阻抗非单调且不可分的情形,建立了模型的均衡公式和约束条件.探讨了模型解的存在性和唯一性特征,并将之表示为一个非线性互补问题,研究非线性互补问题的解得到结论:其唯一性不保证.最后用一个小型网络进行测试来表现模型的特征,测试结果表明出行阻抗的非单调、不可分性质通过影响出行时间方差来影响网络均衡流分配,造成均衡路段和路径阻抗的增加.  相似文献   

5.
采用均匀设计试验方案对影响边坡稳定性的因素进行测量,既能节约取样开支,又能得到均匀分散且具有代表性的小样本数据.对该小样本数据结合偏最小二乘回归方法,建立了边坡稳定性系数与各影响因素的非线性回归模型.通过对模型结构、变量投影重要性指标、相对残差值及拟合值的分析发现,基于均匀设计试验利用偏最小二乘回归法可用于对边坡稳定性的分析预测.  相似文献   

6.
西安市城市居民生活用水量的实证分析   总被引:2,自引:0,他引:2  
基于多元回归分析方法,以西安市为例,探讨影响城市生活用水量的影响因素,建立了基于多元线性回归分析的城市生活用水模型,并且采用来自《西安统计年鉴》的统计数据作为样本,进行实证分析.通过回归拟合结果分析证明,城市居民人口和居住面积两项指标对城市生活用水量的影响最为显著,研究结果证实了所建立的模型回归效果显著,误差较小,结果令人满意.  相似文献   

7.
利用B型超声对520例胎儿的股骨长度、腹围的测量数据,建立多元非线性回归模型,并用此模型对982例胎儿进行实例验证、分析,得到精确度极高的预测结果,为临床应用提供了新的胎儿体重预测方法.  相似文献   

8.
非线性再生散度模型的几何结构及其渐近推断   总被引:2,自引:0,他引:2  
本文基于唐年胜等(1999)对非线性再生散度模型在欧氏空间建立的微分几何结构导出了与估计有关的随机展开以及与统计曲率有关的若干渐近推断,推广了韦博成等人关于非线性回归模型和指数族非线性模型的相应结果.  相似文献   

9.
该文用微分几何方法对AR(q)误差非线性回归模型若干二 阶渐近性质进行了研究. 作者基于Fisher信息阵在欧氏空间定义了内积,并在期望参数空间建立了几何结构. 基于上述几何结构,给出了AR(q)误差非线性回归模型若干二阶渐近性质的曲率表示. 将前人的一些结果推广到AR(q)误差非线性回归模型.   相似文献   

10.
基于非线性光滑支持向量回归机研究了人口老龄化问题.首先介绍了非线性光滑支持向量回归机(NSSVR);其次,提出了人口老龄化影响体系,利用主成分分析(PCA),在体系基础上提取出对老龄化影响明显的9个指标;再次,通过非线性光滑支持向量回归机模型建立了老龄化率与9个影响指标间的相互关系;最后,用非线性光滑支持向量回归机模型对未来人口老龄率进行预测.实证表明,方法具有很好的预测效果.  相似文献   

11.
The first-order nonlinear autoregressive model is considered and a semiparametric method is proposed to estimate regression function. In the presented model, dependent errors are defined as first-order autoregressive AR(1). The conditional least squares method is used for parametric estimation and the nonparametric kernel approach is applied to estimate regression adjustment. In this case, some asymptotic behaviors and simulated results for the semiparametric method are presented. Furthermore, the method is applied for the financial data in Iran’s Tejarat-Bank.  相似文献   

12.
The aim of this paper is to study the tests for variance heterogeneity and/or autocorrelation in nonlinear regression models with elliptical and AR(1) errors. The elliptical class includes several symmetric multivariate distributions such as normal, Student-t, power exponential, among others. Several diagnostic tests using score statistics and their adjustment are constructed. The asymptotic properties, including asymptotic chi-square and approximate powers under local alternatives of the score statistics, are studied. The properties of test statistics are investigated through Monte Carlo simulations. A data set previously analyzed under normal errors is reanalyzed under elliptical models to illustrate our test methods.  相似文献   

13.
Multivariate longitudinal data arise frequently in a variety of applications, where multiple outcomes are measured repeatedly from the same subject. In this paper, we first propose a two-stage weighted least square estimation procedure for the regression coefficients when the random error follows an irregular autoregressive(AR) process, and establish asymptotic normality properties for the resulting estimators. We then apply the smoothly clipped absolute deviation(SCAD) variable selection approach to determine the order of the AR error process. We further propose a test statistic to check whether multiple responses are correlated at the same observation time, and derive the asymptotic distribution of the proposed test statistic. Several simulated examples and real data analysis are presented to illustrate the finite-sample performance of the proposed method.  相似文献   

14.
This paper constructs a set of confidence regions of parameters in terms of statistical curvatures for AR(q) nonlinear regression models. The geometric frameworks are proposed for the model. Then several confidence regions for parameters and parameter subsets in terms of statistical curvatures are given based on the likelihood ratio statistics and score statistics. Several previous results,, such as [1] and [2] are extended to AR(q)nonlinear regression models.  相似文献   

15.
线性回归分析是数理统计学的基本内容之一,但传统数理统计学中的线性回归分析,是建立在非模糊的随机数据上的线性回归估计和回归系数检验。而现实经济社会中大量存在含有模糊或灰色等不分明性的数据,面对这类不分明性数据,简单地使用传统的统计分析方法显然是不足取的。要想较为科学合理地分析与决策,需要利用灰色系统的相关理论,应用于随机系统信息,从而建立灰色线性回归估计、预测和灰色回归系数检验的基本理论方法,并把该方法应用于金融分析实例中,与经典线性回归分析方法进行对比,足见灰色线性回归方法能够提供比经典线性回归较多的有效信息,从而提出处理不分明数据新的方法。  相似文献   

16.
The traditional standard stochastic system models, such as the autoregressive (AR), moving average (MA) and autoregressive moving average (ARMA) models, usually assume the Gaussian property for the fluctuation distribution, and the well-known least squares method is applied on the basis of only the linear correlation data. In the actual sound environment system, the stochastic process exhibits various non-Gaussian distributions, and there exist potentially various nonlinear correlations in addition to the linear correlation between input and output time series. Consequently, the system input and output relationship in the actual phenomenon cannot be represented by a simple model. In this study, a prediction method of output response probability for sound environment systems is derived by introducing a correction method based on the stochastic regression and fuzzy inference for simplified standard system models. The proposed method is applied to the actual data in a sound environment system, and the practical usefulness is verified.  相似文献   

17.
组间方差和自相关系数的齐性是纵向数据分析的基本假设之一,然而这种假设需要进行统计检验. Zhang \&; Weiss$^{[15]}$ 讨论了线性随机效应模型的组间和组内方差齐性的检验问题;林金官 \&; 韦博成$^{[10]}$ 研究了具有AR(1)误差但没有随机效应的非线性模型的自相关系数的齐性检验.该文研究具有随机效应和AR(1)误差的非线性模型的组间方差和自相关系数的齐性检验问题,构造了几个score检验统计量, 并通过Monte Carlo模拟方法研究了检验统计量的性质.最后利用该文的方法分析一组实际数据和一组模拟数据.  相似文献   

18.
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.  相似文献   

19.
High-dimensional data with hundreds of thousands of observations are becoming commonplace in many disciplines. The analysis of such data poses many computational challenges, especially when the observations are correlated over time and/or across space. In this article, we propose flexible hierarchical regression models for analyzing such data that accommodate serial and/or spatial correlation. We address the computational challenges involved in fitting these models by adopting an approximate inference framework. We develop an online variational Bayes algorithm that works by incrementally reading the data into memory one portion at a time. The performance of the method is assessed through simulation studies. The methodology is applied to analyze signal intensity in MRI images of subjects with knee osteoarthritis, using data from the Osteoarthritis Initiative. Supplementary materials for this article are available online.  相似文献   

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