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multivariate analysis相关的网络例句

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与 multivariate analysis 相关的网络例句 [注:此内容来源于网络,仅供参考]

In the aspect of multivariate modeling, three forms of multivariate GARCHSK model includes vector form, diagonal form and simplify form, are put forward and compared. The famous dimension disaster exists in multivariate GARCHSK model also. Based on Independent Component Analysis, multivariate volatilities of conditional higher moments are estimated through IC-GARCHSK model, which make dynamic relation of higher moment risk between multi-assets to be possible.

鉴于多元 GARCHSK 模型存在严重的"维数灾难"问题,基于独立成分分解技术提出 IC-GARCHSK 模型,给出多元条件高阶矩波动率的估计方法,使得同时度量多个资产高阶矩风险之间动态关系成为可能,为利用组合投资方式分散高阶矩风险的影响奠定了方法论基础。

The statistical difference of proinsulin rather than HOMA index was found among the patients of various Gensini's score group (Gensini's score was examined as a categorical variable classified by tertile values) and significantly stenosed vessels group by means of the results of analysis of covariate variance after adjusting for age, sex and body mass index (p<0.05), and the partial correlation coefficient between proinsulin level and Gensini's score, the number of significantly stenosed vessels after adjusting for age, sex and body mass index was 0.3156 (P<0.01) and 0.2752 (P<0.05) respectively. Multivariate linear regression analysis indicated that the level of proinsulin was positively correlated with the Gensini's score (P<0.01). The results of multivariate stepwise Logistic indicated that the proinsulin was the independent risk factor for the coronary heart disease, and the odds ratio (95% confidence interval) was 2.268 (1.253~4.105)(P=0.007), however, the HOMA was refused by the final model.

年龄、性别与体重指数为控制变量的协方差分析结果显示,胰岛素原的水平在不同的Gensini评分组、冠状动脉病变血管数分组中分布有统计学差异(P<0.05),偏相关分析示胰岛素原的含量与Gensini评分与病变血管数显著正相关,其偏相关系数分别为0.3156(P<0.01)与0.2752(P<0.05),而HOMA指数与两种评分的相关未有统计学意义;多因素线性逐步回归分析结果示胰岛素原水平与Gensini评分独立正相关(P<0.01);多因素Logistic回归分析显示,胰岛素原的水平为冠心病的独立的危险因素,其OR值及其95%可信区间为2.268(1.253~4.105)(P<0.01),HOMA指数未进入模型。

The questionnaire method and the interview menthod were used to gain the tourist data, the quota sampling method was used in sampling survey, the principal component analysis method was used to measure the various variables, the statistical methods such as linear regression analysis, multivariate linear regression analysis, single factor variance analysis and logistic regression analysis were used to analyzes the relationship between various variables.

具体来说,在获取游客数据时采用了问卷调查法和访谈法,在抽样调查时采用了配额抽样方法;对各变量进行测度时使用了主成分分析法;在分析各变量之间相互关系时采用一元线性回归分析、多元线性回归分析、单因素方差分析及Logistic回归分析等统计方法。

There are several methods can be applied in symptom complex study: Principal component analysis, Factor analysis, Cluster analysis, Regression analysis, and Correspondence analysis, etc. In this article, the author introduces the application of multivariate statistical analysis in TCM symptom complex normalization research in the following four aspects: establishing the basic symptom, filtering optimization index, settling the weight of the index, and setting up the mathematical model.

本文从确立基本证型、筛选优化指标、确立优化指标的权重、建立证候数学模型等4个环节上介绍了多元统计分析在中医证候诊断标准领域的应用,并指出:多元统计分析是研究多因素和多指标问题的统计分析方法,证候诊断学正是研究疾病的多种证型与多种症状之间的关系问题,因此,可以将多元统计分析应用于中医证候的规范化研究中。

Univariate and multivariate analysis demonstrated that age and myeloid antigen expression were adverse prognostic factors.

单因素和多因素分析显示年龄和髓系抗原表达是T-LBL的不良预后因素。

The prognostic factors were identified and stratified by univariate and multivariate analysis.

通过单因素和多因素分析筛选并层别化预后影响因素。

Contents: Multivariate statistical analysis is developed quickly on the foundation of mathematical statistics. It is widely applied in every field of natural science and social science and it is the indispensable important tool to handle multivariate data.

主要内容:多元统计分析是在数理统计学的基础上迅速发展起来的一门学科,已广泛应用于自然科学和社会科学的各个领域,是处理多维数据不可缺少的重要工具。

MR images was analyzed include tumor shape,margin, internal enhancement characteristics,distribution,and time-signal intensity curves,maximam enhancement ratio,early enhancement ratio and so on.The ADCs of lesions were calculated on ADC maps.Univariate and multivariate analysis of MR imaging data were performed to find the strongest discriminators and the Logestic regression model was established to predict the probabilities for malignancy.

由放射科医生采用双盲法阅片,根据乳腺MR影像报告及数据系统(BI-RADS MRI),将病变按照不同形态学表现分为肿块和非肿块性病变两组,分析形态学表现(形状、边缘、分布特征、内部增强特征)、血流动力学表现(时间-信号强度曲线类型、最大增强率、达峰时间、早期增强率),并结合ADC值,应用SPSS15.0软件进行单变量及多变量分析,挖掘有意义恶性征象,建立回归模型,计算其敏感性、特异性、准确性、阳性预测值和阴性预测值。

Learning disorders ; Psychosomatic medicine ; Health education ; Multivariate analysis ; Student

学习障碍;心身医学;多元分析;卫生教育;学生

Keywords Learning disorders;Psychosomatic medicine;Health education;Multivariate analysis;Student

学习障碍;心身医学;多元分析;卫生教育;学生

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随着死亡的吉他手Schuldiner接受主唱的职务,乐队在现实中树立了重要的影响。

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关闭眼睛,深呼吸,一切不再是梦想,犹如。。。。。。