并利用逐步回归分析方法,建立大豆产量的预测模型,找出影响大豆产量的主要气象因子。
Taking advantage of stepwise regression, we find the main meteorological factors which affect the soybean output and establishes a calculate model.
在逐步回归模型中,术前感觉功能正常是正向预测因子,而工伤保险赔偿是完全临床治愈的负性预测因子。
In the stepwise regression model, preoperative normal sensory function was a positive predictor and worker's compensation a negative predictors of overall clinical success.
用逐步回归方法筛选影响空间分量和时间系数的环境和经济因子,组建因子结构模型。
The environmental and economic factors affecting the space component and the time coefficient are sieved by stepwise regression, and factor structure models are established.
并用双重筛选逐步回归的方法分析了环境(气候和土壤)因子与植物群落生活型谱梯度的关系,建立了相应的数学模型。
The relationship between environmental factors (climate and soil) and plant life form gradient was analysed by doub sieving progressive regression method, and mathematical models were set up.
为了检验其预报效果,根据相同的预报因子和历史样本,建立了相应的逐步回归预报模型。
In order to check the prediction effect, the stepwise regressive equation prediction model was established with the same prediction elements and historical samples.
通过多元线性回归模型,得出了多因子复合流变方程。
A multivariate regression equation was deduced with a multivariate linear regression model.
提出了采用遗忘因子的自回归(AR)模型的功角预测方法。
The rotor angle predicting method adopting the forgetting index of auto regression (AR) model arithmetic is presented.
本文根据实地调查资料,利用因子分析法和回归模型研究了社会资本对农产品购销商经营绩效的影响。
Using Factor analysis and regression model, the authors conducted an empirical study on the effect of social capital on the performance of agricultural traders.
在分析数据的基础上,选择了相关遥感因子和定性因子,并通过一系列模型的检验与修正,建立了公顷蓄积量估测的最优多元线性回归模型。
Based on the analysing of the data, selected relevant factors, made a series of tests and amendments with models, then created forest volume estimation optimal multivariate linear regression model.
为解决模型实际应用中的问题,笔者引用了积分回归的概念,对传统模型的因子集进行了扩充。
To resolve the problem in the application of the models, the author expanded the classical factor set of models by introducing the concept of integral regression.
将这种新的预测模型(主成分神经网络预报模型)与同样根据这些预报因子建立的逐步回归预报模型进行了对比分析。
Predictive capability between the new model (principal components ANN model) and linear regression model for the same predictors is discussed based on the independent samples and historical samples.
通过温热因子和小麦产量的相关分析及最优回归模型的建立,结果表明在降水较少的地区,温热增产作用未能正常发挥;
Through correlation analysis of temperature, heat and wheat yield in Shaanxi province, an optimum regression model of them is established.
基于此,本文构建了条件双因子评价模型,并且以中国全部54只封闭式基金为样本采用面板数据回归技巧验证了该模型的有效性。
This paper builds a conditional two-factor measure model, and proves the efficiency of this model using panel data regression skill. The samples are 54 Chinese close-end funds.
用1951- 1995年的45年资料建立的二因子回归预报模型的复相关系数可达到0.66。
The regression model based on 45 years data (1951-1995) with the two parameters has a multiple correlation coefficient of 0. 66.
其次,研究采用我国2006年私营企业调查的数据,通过因子分析、多元回归分析等方法对模型所包含的假设进行了实证检验。
Secondly, using the 2006 survey of Chinese private enterprises, this study attests those hypotheses through several methods such as factor analysis and multiple regression analysis.
根据实测的数据,采用一元线性、多元线性和非线性回归进行拟合,得到34个红海榄幼苗主要形态因子和生物量的回归模型。
Based on the data observed, 34 regression models on the morphological variables and biomass of the seedlings were set up using linear, multilinear and non linear regression.
根据野外观测资料及气象站观测的气象因子,利用多元统计方法,建立了各可燃物类型地表可燃物含水率与其相关的气象因子之间的回归模型。
According to the measurement of dead fuel moistures and meterological factors in field, by the means of multi-factors statistics, the models of dead fuel moisture were developed.
在因子范围服从对数正态分布下,应用线性回归技术和极大似然法建立了模型参数的测定方法。
Parameters of the model are measured by a linear regression technique and a maximum likelihood method.
一些组合的遗传模型的离回归测验显著,表明除了基因的加性-显性作用外,还有一些因子对充实度有影响。
The goodness of fit test of genetic model was significant, indicated that besides additive-dominance, other factors, such as epistasis, might affect grain plumpness.
最后,通过采用因子分析、方差分析、多元回归分析等统计方法对所提出的概念模型和研究假设进行了验证和分析。
Finally, by using factor analysis, variance analysis and multiple regression analysis, this paper verifies the above conceptual model and research hypothesis.
建立一个包含这些因子的垃圾产量的多元线性回归分析预测模型,并对2004~2010年的垃圾产量进行预测。
The output from 2004 to 2010 was predicted by means of a multivariate regression linear model, including the factors. The results show the model with a higher precision and the better practicability.
采用三因素五水平二次回归正交旋转组合设计,研究玉米品种、密度、施肥措施对西昌地区玉米产量形成的作用效应,建立回归模型并分析各因子的作用规律。
Quadratic orthogonal regressive rotation design of three factors is applied to study the effect of varieties, density and fertilization to maize yield in Xichang ecological area.
采用三因素五水平二次回归正交旋转组合设计,研究玉米品种、密度、施肥措施对西昌地区玉米产量形成的作用效应,建立回归模型并分析各因子的作用规律。
Quadratic orthogonal regressive rotation design of three factors is applied to study the effect of varieties, density and fertilization to maize yield in Xichang ecological area.
应用推荐