共查询到20条相似文献，搜索用时 15 毫秒
1.
José García Román Salmerón Catalina García María del Mar López Martín 《Revue internationale de statistique》2016,84(2):245-266
Ridge estimation (RE) is an alternative method to ordinary least squares when there exists a collinearity problem in a linear regression model. The variance inflator factor (VIF) is applied to test if the problem exists in the original model and is also necessary after applying the ridge estimate to check if the chosen value for parameter k has mitigated the collinearity problem. This paper shows that the application of the original data when working with the ridge estimate leads to non‐monotone VIF values. García et al. (2014) showed some problems with the traditional VIF used in RE. We propose an augmented VIF, VIFR(j,k), associated with RE, which is obtained by standardizing the data before augmenting the model. The VIFR(j,k) will coincide with the VIF associated with the ordinary least squares estimator when k = 0. The augmented VIF has the very desirable properties of being continuous, monotone in the ridge parameter and higher than one. 相似文献
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Ordered categorial predictors are a common case in regression modelling. In contrast to the case of ordinal response variables, ordinal predictors have been largely neglected in the literature. In this paper, existing methods are reviewed and the use of penalized regression techniques is proposed. Based on dummy coding two types of penalization are explicitly developed; the first imposes a difference penalty, the second is a ridge type refitting procedure. Also a Bayesian motivation is provided. The concept is generalized to the case of non-normal outcomes within the framework of generalized linear models by applying penalized likelihood estimation. Simulation studies and real world data serve for illustration and to compare the approaches to methods often seen in practice, namely simple linear regression on the group labels and pure dummy coding. Especially the proposed difference penalty turns out to be highly competitive. 相似文献
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回归分析是数理统计中的一个重要内容,是利用统计学原理寻求隐藏在随机现象中的统计规律的计算方法和理论,它在各个学科领域以及社会经济各部门都得到广泛应用。运用回归分析建立回归模型,并通过逐步回归求得"最优"结果,利用最优回归模型对规模以上企业效益未来发展进行预测,从而为有关部门的决策提供一定的科学依据。 相似文献
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Dynamic processes are crucial in many empirical fields, such as in oceanography, climate science, and engineering. Processes that evolve through time are often well described by systems of ordinary differential equations (ODEs). Fitting ODEs to data has long been a bottleneck because the analytical solution of general systems of ODEs is often not explicitly available. We focus on a class of inference techniques that uses smoothing to avoid direct integration. In particular, we develop a Bayesian smooth-and-match strategy that approximates the ODE solution while performing Bayesian inference on the model parameters. We incorporate in the strategy two main sources of uncertainty: the noise level of the measured observations and the model approximation error. We assess the performance of the proposed approach in an extensive simulation study and on a canonical data set of neuronal electrical activity. 相似文献
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文中论述了南昌市经济发展与物流需求之间的内在关系,在定性分析的基础上,选取适当的物流指标与经济指标,采用回归分析法进行定量分析,结合实际,揭示经济发展过程中,进行固定资产投资、最大程度的满足市场扩大的需求之间的因果关系,以便进行相关经济预测及分析。 相似文献
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土工试验数据处理通常是通过繁琐计算与作图来完成,且要求及时、准确。线性回归处理法通过一定的数理关系有效简化数据处理的计算与作图过程。通过大量的剪切、液塑限试验数据处理表明,其结果是准确的、值得信赖的,它通过线性回归简化繁琐计算,使作图也变得简单。本文主要针对土工试验中的线性回归应用进行分析,从大量的剪切、液塑限联合试验中论证其结果的准确性。 相似文献
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A common strategy within the framework of regression models is the selection of variables with possible predictive value, which are incorporated in the regression model. Two recently proposed methods, Breiman's Garotte (B reiman , 1995) and Tibshirani's Lasso (T ibshirani , 1996) try to combine variable selection and shrinkage. We compare these with pure variable selection and shrinkage procedures. We consider the backward elimination procedure as a typical variable selection procedure and as an example of a shrinkage procedure an approach of V an H ouwelingen and L e C essie (1990). Additionally an extension of van Houwelingens and le Cessies approach proposed by S auerbrei (1999) is considered. The ordinary least squares method is used as a reference.
With the help of a simulation study we compare these approaches with respect to the distribution of the complexity of the selected model, the distribution of the shrinkage factors, selection bias, the bias and variance of the effect estimates and the average prediction error. 相似文献
With the help of a simulation study we compare these approaches with respect to the distribution of the complexity of the selected model, the distribution of the shrinkage factors, selection bias, the bias and variance of the effect estimates and the average prediction error. 相似文献
9.
利用多元线性回归的方法和SPSS软件,对湖南省的物流需求情况进行了预测与分析。根据建立的模型,预测了未来五年湖南省的物流需求,分析了影响物流需求的因素。研究结果可为湖南省物流产业的科学规划提供一定的建议。 相似文献
10.
当前,房地产业已经成为我国国民经济支柱性产业。然而,不断上涨的房地产价格,在一定程度上影响或制约着我国经济的发展。本文先对我国房地产市场发展状况进行分析,然后从计量经济学角度分析了房地产价格上涨的成因,并针对模型出现的自相关和共线性问题,灵活采用岭回归分析方法,使得结果更符合实际,最后在此基础上提出相应对策与建议。 相似文献
11.
Sylvain Sardy 《Revue internationale de statistique》2008,76(2):285-297
Whether doing parametric or nonparametric regression with shrinkage, thresholding, penalized likelihood, Bayesian posterior estimators (e.g., ridge regression, lasso, principal component regression, waveshrink or Markov random field ), it is common practice to rescale covariates by dividing by their respective standard errors ρ. The stated goal of this operation is to provide unitless covariates to compare like with like, especially when penalized likelihood or prior distributions are used. We contend that this vision is too simplistic. Instead, we propose to take into account a more essential component of the structure of the regression matrix by rescaling the covariates based on the diagonal elements of the covariance matrix Σ of the maximum-likelihood estimator. We illustrate the differences between the standard ρ- and proposed Σ-rescalings with various estimators and data sets. 相似文献
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劳动力工资水平作为关乎国计民生的重大问题,一直受到政府部门和社会各界的高度关注。文章采用理论分析与实证研究相结合的研究方法,利用专业的计量经济学软件Eviews,分析出与劳动力工资水平密切相关的宏观因素。 相似文献
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We study a “direct test” of Chu and White (1992) proposed for detecting changes in the trend of a linear regression model. The power of this test strongly depends on a suitable estimation of the variance of the error variables involved. We discuss various types of variance estimators and derive their asymptotic properties under the null-hypothesis of “no change” as well as under the alternative of “a change in linear trend”. A small simulation study illustrates the estimators' finite sample behaviour. 相似文献
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基于双变量线性回归模型的物流需求预测——以内蒙古为例 总被引：1，自引：0，他引：1
物流产业作为综合性很强的经济产业,无论是宏观决策,还是物流企业的规划和经营决策,都需要以正确的预测为前提。针对物流需求的特点。运用双变量线性回归模型对物流需求进行预测,并以内蒙古为例进行了实证。 相似文献
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本文针对以X公司预算编制存在的问题,提出了解决方案。依据X公司近五年的财务数据,通过建立多元一次回归模型,选择最相关的研发费用因素来准确的预测出X公司2014年度研发费用总额。 相似文献
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Correlation is an important statistical issue for the Ordinary Least Squares estimates and for data‐reduction techniques, such as the Factor and the Principal Components analyses. In this paper we propose new indicators for the multicollinearity problem in the multiple linear regression model. 相似文献
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运用因子分析方法提取了影响合作创新的四个方面的因素,通过多元线性回归模型对企业高校合作创新的相关假设进行验证,并对检验结果进行了分析和探讨。 相似文献
18.
Bahadır Yüzbaşı Mohammad Arashi S. Ejaz Ahmed 《Revue internationale de statistique》2020,88(1):229-251
In this study, we suggest pretest and shrinkage methods based on the generalised ridge regression estimation that is suitable for both multicollinear and high-dimensional problems. We review and develop theoretical results for some of the shrinkage estimators. The relative performance of the shrinkage estimators to some penalty methods is compared and assessed by both simulation and real-data analysis. We show that the suggested methods can be accounted as good competitors to regularisation techniques, by means of a mean squared error of estimation and prediction error. A thorough comparison of pretest and shrinkage estimators based on the maximum likelihood method to the penalty methods. In this paper, we extend the comparison outlined in his work using the least squares method for the generalised ridge regression. 相似文献
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