共查询到20条相似文献,搜索用时 46 毫秒
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陈继光 《数学的实践与认识》2016,(19):199-204
针对面板数据灰色关联决策评价模型的关联度计算问题,在传统的面板数据灰色关联决策评价模型的基础上,构建评价对象的指标时间数据的累加序列,通过指标时间累加生成速率序列构造面板数据灰色生成速率关联决策模型,采用生成速率序列的接近性表征原始数据序列的动态变化趋势.通过灰色累加生成速率关联决策方法扩展到面板数据分析,解决了小样本面板数据的灰色评价分析问题,将这种方法应用于南四湖入湖河流水质面板数据质量评价中,经实例计算验证了面板数据灰色累加生成速率关联决策评价模型的稳定性、合理性和实用性为水环境面板数据质量分析评价提供了可行的计算思路和方法. 相似文献
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《数学的实践与认识》2015,(16)
针对传统因子分析只限于对截面数据进行分析研究存在的不足作了改进.通过建立基于Topsis法改进的因子分析模型对面板数据进行研究分析.以每一年的横截面数据因子综合得分最高和最低分别作为最优和最劣向量,通过Topsis法求出每个样本因子综合得分与最优因子方案接近程度.以中国加入WTO后的经济增长为例,用模型的最优因子方案接近程度来刻画各个省份2004年-2012年的经济发展状况,研究得到的结论是大部分省份与最优因子方案接近度较大. 相似文献
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为了比较多个待评价对象在不同时刻的发展水平,以及在某一时间段内的总体发展水平,进行动态评价显得十分必要.传统TOPSIS评价方法仅考虑数据序列之间的距离关系,没有考虑距离间的相关性,为解决以上问题,文章将集对分析联系度思想引入TOPSIS,采用联系向量距离代替欧氏距离计算贴近度,加入时间维度,提出基于联系度的动态TOPSIS评价方法.该方法不仅可以得到反映评价指标值差异程度的评价值及排序结果,还可以得到反映评价指标值增长程度的评价值及排序结果,同时还能得到同时考虑以上两种情况的综合评价值及排序结果.将该方法应用于2016-2020年长江经济带绿色发展水平评价,通过实例验证了该方法在实际应用中的有效性. 相似文献
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高雄飞 《数学的实践与认识》2018,(8)
为了对这种具有非线性特性的时间序列进行预测,提出一种基于混沌最小二乘支持向量机.算法将时间序列在相空间重构得到嵌入维数和时间延滞作为数据样本的选择依据,结合最小二乘法原理和支持向量机构建了基于混沌最小二乘支持向量机的预测模型.利用此预测模型对栾城站土壤含水量时间序列进行了预测.结果表明,经过相空间重构优化了数据样本的选取,通过模型的评价指标,混沌最小二乘支持向量机的预测模型能精确地预测具有非线性特性的时间序列,具有很好的理论和应用价值. 相似文献
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涉农企业信用评价动态指标隶属度向量判别研究 总被引:2,自引:0,他引:2
对涉农企业信用评价中的动态指标的隶属度向量进行判别研究.首先借鉴X-12-A砒MA季节调整法的思想对信用数据进行剥离,构建一种过程连续性的动态信用指标;其次通过时间序列三指数平滑模型对动态信用数据的变化进行预测,得到动态信用指标隶属度向量;再次,结合熵权-AHP法确定的权重,确定动态信用指标的综合隶属度向量;最后实证检验了方法在企业信用评价中应用的有效性. 相似文献
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在分析了制造企业创新能力评价指标体系的基础上进行企业调查,对收集到的不同类型制造企业的完整数据进行整理,因子分析整理后得到9个综合因子表述原数据,以减少数据处理及问题分析的复杂性.利用支持向量机作为分类器,并使用已有的企业数据作为训练样本,创建了基于支持向量机的制造企业创新能力评价模型.实验结果表明采用径向基函数和多项式函数作为核函数,此模型具有很好的分类性能,可作为制造企业创新能力的评价工具. 相似文献
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小企业信用风险评价既是银行风险管理问题,又事关经济社会稳定。针对小企业贷款实践中,违约样本远少于非违约样本、且违约客户误判对银行影响较大的现实,采用不均衡支持向量机对小企业信用风险评价指标进行赋权,进而构建了能有效区分违约客户、非违约客户的评价模型。根据有无特定评价指标、特定评价指标数值变化对贷款小企业违约状态的影响程度赋权;反映了对违约状态影响越大、评价指标权重越大的赋权思路。将违约样本正确识别率、违约样本的准确率与查全率等因素作为支持向量机赋权模型中客户识别率的度量标准,改变了样本数据不均衡所导致的样本总体精度很高、违约样本精度反而不高的现象。研究结果表明:行业景气指数、资本固定化比率、净利润现金含量、恩格尔系数、营业利润率等评价指标对小企业信用风险的影响较大。 相似文献
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基于因子分析的中国寿险公司经营效率综合评价 总被引:1,自引:1,他引:0
刘璐 《数学的实践与认识》2010,40(8)
利用财务指标法评价寿险公司绩效的一个重要特点就是主观赋权,而主观赋权一方面会导致对某个或某些因素过高或过低的估计,使评价结果不能如实反映寿险公司的真实情况,另一方面会诱使寿险公司粉饰或追求权重较高的指标.利用因子分析法,以2007年在我国境内开展业务的34家寿险公司作为样本,选择17个指标构建截面数据体系,对样本公司的风险水平和经营绩效进行评价.结果表明,老牌中资寿险公司保持着强大的综合实力,仍然是我中国人寿险市场的主导;外资寿险公司逐步加大规模扩张,资产管理能力不容轻视. 相似文献
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Factoring Factor Maps 总被引:1,自引:0,他引:1
A noninjective bounded-to-one factor map from an irreducibleshift of finite type onto a sofic system can be factored asa composition of other such maps in only finitely many ways(up to isomorphism). This generalizes to factor maps from systemswith canonical coordinates to finitely presented dynamical systems. 相似文献
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Matthew M. Tibbits Chris Groendyke Murali Haran John C. Liechty 《Journal of computational and graphical statistics》2013,22(2):543-563
Markov chain Monte Carlo (MCMC) algorithms offer a very general approach for sampling from arbitrary distributions. However, designing and tuning MCMC algorithms for each new distribution can be challenging and time consuming. It is particularly difficult to create an efficient sampler when there is strong dependence among the variables in a multivariate distribution. We describe a two-pronged approach for constructing efficient, automated MCMC algorithms: (1) we propose the “factor slice sampler,” a generalization of the univariate slice sampler where we treat the selection of a coordinate basis (factors) as an additional tuning parameter, and (2) we develop an approach for automatically selecting tuning parameters to construct an efficient factor slice sampler. In addition to automating the factor slice sampler, our tuning approach also applies to the standard univariate slice samplers. We demonstrate the efficiency and general applicability of our automated MCMC algorithm with a number of illustrative examples. This article has online supplementary materials. 相似文献
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Aditya Mishra Dipak K. Dey Kun Chen 《Journal of computational and graphical statistics》2017,26(4):814-825
In multivariate regression models, a sparse singular value decomposition of the regression component matrix is appealing for reducing dimensionality and facilitating interpretation. However, the recovery of such a decomposition remains very challenging, largely due to the simultaneous presence of orthogonality constraints and co-sparsity regularization. By delving into the underlying statistical data-generation mechanism, we reformulate the problem as a supervised co-sparse factor analysis, and develop an efficient computational procedure, named sequential factor extraction via co-sparse unit-rank estimation (SeCURE), that completely bypasses the orthogonality requirements. At each step, the problem reduces to a sparse multivariate regression with a unit-rank constraint. Nicely, each sequentially extracted sparse and unit-rank coefficient matrix automatically leads to co-sparsity in its pair of singular vectors. Each latent factor is thus a sparse linear combination of the predictors and may influence only a subset of responses. The proposed algorithm is guaranteed to converge, and it ensures efficient computation even with incomplete data and/or when enforcing exact orthogonality is desired. Our estimators enjoy the oracle properties asymptotically; a non-asymptotic error bound further reveals some interesting finite-sample behaviors of the estimators. The efficacy of SeCURE is demonstrated by simulation studies and two applications in genetics. Supplementary materials for this article are available online. 相似文献
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A Bayesian approach is developed to assess the factor analysis model. Joint Bayesian estimates of the factor scores and the structural parameters in the covariance structure are obtained simultaneously. The basic idea is to treat the latent factor scores as missing data and augment them with the observed data in generating a sequence of random observations from the posterior distributions by the Gibbs sampler. Then, the Bayesian estimates are taken as the sample means of these random observations. Expressions for implementing the algorithm are derived and some statistical properties of the estimates are presented. Some aspects of the algorithm are illustrated by a real example and the performance of the Bayesian procedure is studied using simulation. 相似文献
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K. N. Ponomarev 《Siberian Mathematical Journal》1991,32(3):449-454
Novosibirsk. Translated from Sibirskii Matematicheskii Zhurnal, Vol. 32, No. 3, pp. 119–125, May–June, 1991. 相似文献
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加速退化因子的研究 总被引:1,自引:0,他引:1
刘合财 《数学的实践与认识》2010,40(12)
主要讨论了可靠性工程中加速退化失效问题中的加速退化因子,给出了Ⅰ、Ⅱ型加速退化因子的定义,并研究了它们之间的关系、性质及其应用. 相似文献
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Maxime Crochemore Lucian Ilie Costas S. Iliopoulos Marcin Kubica Wojciech Rytter Tomasz Waleń 《European Journal of Combinatorics》2013
The Longest Previous Factor array gives, for each position i in a string y, the length of the longest factor (substring) of y that occurs both at i and to the left of i in y. The Longest Previous Factor array is central in many text compression techniques as well as in the most efficient algorithms for detecting motifs and repetitions occurring in a text. Computing the Longest Previous Factor array requires usually the Suffix Array and the Longest Common Prefix array. We give the first time–space optimal algorithm that computes the Longest Previous Factor array, given the Suffix Array and the Longest Common Prefix array. We also give the first linear-time algorithm that computes the permutation that applied to the Longest Common Prefix array produces the Longest Previous Factor array. 相似文献