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回归残差
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  regression residual
     Principal Component Regression Residual Artificial Neural Network Calibration Algorithm Applied in Near Infrared Fast Measurement of Gasoline Octane Number
     主成分回归残差神经网络校正算法用于近红外光谱快速测定汽油辛烷值
短句来源
     A novel calibration algorithm, PCRRANN (principal component regression residual artificial neural network) method, was proposed based on the intrinsic non linearity of the prediction of gasoline octane number, and then applied to the calibration of the prediction model of the near infra red measurement of gasoline octane number.
     根据汽油辛烷值预测体系本身的非线性特点 ,提出主成分回归残差神经网络校正算法(principalcomponentregressionresidualartificialneuralnetwork ,PCRRANN)用于近红外测定汽油辛烷值的预测模型校正。
短句来源
     The moisture value was modified according to a formula gained from regression analysis, and the R square was computed, significance of regression and regression residual were tested. The result indicated that it is feasible to modify the moisture value of bamboo strip according to the equation y=1.172x-8.843.
     根据烘干法通过线性回归分析对测量结果进行了修正,并计算了拟合优度,检验了回归关系的显著性和回归残差的分布,结果表明,用木材测湿仪测量竹篾含水率按回归方程y=1.172x-8.843修正是可行的。
短句来源
     This study was undertaken to determine the degree of importance of plant families in the medicinal plants of Shiwandashan Natural Reserve,Guangxi Province,China. A regression residual analysis was carried out on the number of medicinal species and the total number of species in each family for 182 angiosperm plant families in the Natural Reserve. According to the residual values the 182 families were divided into 114 high use families and 68 low use families.
     本研究旨在确定广西十万大山自然保护区药用植物所在各科的重要程度,用回归残差分析法对保护区182科被子植物中各科的植物种数和药用植物种数之间的关系进行了分析,根据残差值将182科分成114个高利用科和68个低利用科。
短句来源
     A regression residual analysis was carried out on the number of medicinal species and the total number of species in each family for 166 angiosperm families in the Natural Reserve. According to the residual values,the 166 families were categorized into 100 high use families and 66 low use families.
     用回归残差分析法对保护区166科被子植物中各科的植物种数和药用植物种数之间的关系进行了分析,根据残差值将166科分成100个高利用科和66个低利用科。
短句来源
  regression residual artificial
     Principal Component Regression Residual Artificial Neural Network Calibration Algorithm Applied in Near Infrared Fast Measurement of Gasoline Octane Number
     主成分回归残差神经网络校正算法用于近红外光谱快速测定汽油辛烷值
短句来源
     A novel calibration algorithm, PCRRANN (principal component regression residual artificial neural network) method, was proposed based on the intrinsic non linearity of the prediction of gasoline octane number, and then applied to the calibration of the prediction model of the near infra red measurement of gasoline octane number.
     根据汽油辛烷值预测体系本身的非线性特点 ,提出主成分回归残差神经网络校正算法(principalcomponentregressionresidualartificialneuralnetwork ,PCRRANN)用于近红外测定汽油辛烷值的预测模型校正。
短句来源
  “回归残差”译为未确定词的双语例句
     s data, and get the parameter estimate of ARMA noise by Hannan-Rissanen s linear procedure, then the estimate is of strong consistency and is of asymptotic normal efficiency for Gaussian series.
     若用所计算得到的回归残差作为数据,采用Hannan-Rissanen的线性估计法求ARMA噪声的参数估计,则本文证明了估计是强相容的,且对正态序列,估计具有渐近正态优效性。
短句来源
     and gives specific algorithm for realizing these two methods of parameler estimation.
     这两种新的估计方法具有最小的回归残差平方和 ,文中给出实现这两种参数估计方法的具体算法 .
短句来源
     A nonlinear combined regression model for predicting daily water consumption was developed by introducing history data of daily water consumption in time series into regression analysis model using temperature and other parameters as variables. Meanwhile,to increase the prediction accuracy,the residual series were analyzed using AR(4) model,and a practical dynamic combined model for predicting daily water consumption was built.
     将时间序列中的日用水量历史数据引入以温度等作变量的回归分析模型,建立了日用水量非线性回归组合预测模型,同时为进一步提高预测精度,用4阶自回归模型对回归残差序列进行时间序列分析,建立了日用水量预测实用动态组合模型。
短句来源
     Contrast of statistic index of residuals shows priority of wavelet denosing.
     多项式回归残差和小波降噪残差统计指标对比表明:在趋势项分离过程中,小波降噪方法优于多项式回归方法。
短句来源
     The regression diagnosis for the event probability regression madal was carried out. It isshowed that probability regression model have no rationality in the sense of statistical forecastingby the distribution of the probability residua and diagnosis amotunts.
     针对事件概率回归模型的特点,用残差分析和统计量诊断的方法归纳了回归残差的非对称分布现象,揭示了这种现象是由高杠杆点所引起,探讨了概率回归模型的残差不合理性的统计天气预报意义,从而提出适用于概率预报问题的事件概率回归改进模型。
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  regression residuals
Inference is complicated, however, by the non-normality of regression residuals, invalidating standard parametric test procedures.
      
It is shown to be consistent when total expenditure and regression residuals are correlated, either because of simultaneity or because of unobserved heterogeneity.
      
H?lderian properties of partial sums of regression residuals
      
There was, however, significant variance in the haloperidol response; plots of the regression residuals showed the most and least responsive animals differed by almost 100% in effect on PPI.
      
Separate regression residuals were then calculated that corrected for individual differences in blood ethanol concentration at the time of withdrawal and baseline HIC severity (i.e.
      
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  regression residual
Regression residual plots were visually inspected to assess assumptions of linearity and homogeneity of variance.
      
Simulation models provide an alternative to regression Residual Effects analysis for taking account of changing weather conditions and N applications.
      
Thus, random selection is captured in the TEV decomposition mainly by the variance of the regression residual.
      
The assumption that the regression residual is uncorrelated with the regressors breaks down and the OLS estimators are inconsistent.
      
The first-stage regression residual measure represents the portion of the credit spread not explained by fundamentals.
      
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In this paper, the method and application of regression are introduced for dam deformation analysis and forecasting.It is shown that the residual series obtained from existing regression analysis does not satisfy the assumption of random quantities, independent distribution with zero means and constant variance σ~2for this reason, the author suggests using AR (P) model of dynamic data processing for the forecasting of residuals. On this basis, a method to modify the regression of dam deformation analysis is...

In this paper, the method and application of regression are introduced for dam deformation analysis and forecasting.It is shown that the residual series obtained from existing regression analysis does not satisfy the assumption of random quantities, independent distribution with zero means and constant variance σ~2for this reason, the author suggests using AR (P) model of dynamic data processing for the forecasting of residuals. On this basis, a method to modify the regression of dam deformation analysis is proposed. It is proved that the present method is valuable and should be further developed. An example is given.

本文透过目前大坝变形中回归方程预报精度不够理想这一现象,通过分析,指出了现有回归分析中所得残差序列不满足相互独立且服从同一正态N(0,σ)分布的要求。为此作者建议用动态分析中的AR(P)模型对回归残差进行模拟,进而提出了对目前回归预报的改进方案。该方案通过一些实例计算表明是一种值得进一步探讨的方向。

Using correlating and synthetic method to analyse meteorological elements of 500hPa, 700hPa and 850hPa of 159 fog days in Chongqing from 1981 to 1987,the main factors and the key area affecting Chongqing fog and the anomalous features of meteorological elements of 24 hours before fog forming have been got in this paper. On the bases of above,the fog being divided into two patterns and the main factors being as independent variables,by using step-by-step residual reduction regression and the model integration,a...

Using correlating and synthetic method to analyse meteorological elements of 500hPa, 700hPa and 850hPa of 159 fog days in Chongqing from 1981 to 1987,the main factors and the key area affecting Chongqing fog and the anomalous features of meteorological elements of 24 hours before fog forming have been got in this paper. On the bases of above,the fog being divided into two patterns and the main factors being as independent variables,by using step-by-step residual reduction regression and the model integration,a fog forecasting model within24 hours has been obtained. Also,a automatic forecasting software system using IBM computer is devised.

本文首先对重庆雾1981~1987年159个例进行500hPa、700hPa、850hPa各气象要素的相关和合成分析,得到了影响重庆雾的主要因子和主要关键区以及雾发生时24小时以前各层要素场的异常特征。在此基础上,对重庆雾进行了分类,用关键区的因子作为自变量,利用逐步回归残差订正和模型集成,建立起重庆雾24小时预报模型,并设计成软件系统,在IBM机上自动预报。

In this paper, about the linear regression model with ARMA noise, the authors have proposed a linear procedure for model identification and parameter estimation using recursion only, and proved that if we take the obtained regressive residual by the previous procedure a.s data, and get the parameter estimate of ARMA noise by Hannan-Rissanen s linear procedure, then the estimate is of strong consistency and is of asymptotic normal efficiency for Gaussian series.

对于有ARMA噪声的线性回归模型,本文给出了只用递推进行模型辨识和参数估计的线性方法。若用所计算得到的回归残差作为数据,采用Hannan-Rissanen的线性估计法求ARMA噪声的参数估计,则本文证明了估计是强相容的,且对正态序列,估计具有渐近正态优效性。

 
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