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加权最小二乘法的英文

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"加权最小二乘法"怎么读用"加权最小二乘法"造句

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  • method of weighted least squares
  • weighted least squares method
  • weighted least-squares method

例句与用法

  • Using iterative reweighted least squares method for evaluating flatness errors
    使用迭代重加权最小二乘法求解平面度误差
  • The results also show that saastamoinen / niell model can remove the most of the tropospheric delay , and then significantly improve the success rate and the reliability of ambiguity resolution . 4
    结果显示,不论在模糊度解算的成功率和可靠性上,还是在计算速度上,加权最小二乘法都优于kalman滤波。
  • Further , based on the method of pre - elimination of parameters , the formulae of the partly - weigthed least squares estimation with constraints on parts of the parameters are derived to include a prior information
    在顾及电离层加权模型的情况下,利用参数消去法,推导了加权最小二乘法估计模糊度实数解的公式。
  • On account of the defects of rigid localization condition and low localization accuracy in double - vessel localization , the paper gives an algorithm of multiple - vessel localization based on weighted least squares
    摘要针对双舰定位存在的定位态势要求高、定位精度低等,提出了基于加权最小二乘法的多舰定位算法。
  • Synthesizing the two identification methods of weighted least square and resricted memory , the mutivariable system recursive estimate algorithems of unknown parameter of autoregressive models in the presence of controlled inputare are given
    摘要将加权最小二乘法和限定记忆两种参数估计方法相综合,给出了多变量系统带控制输入的自回归模型未知参数的递推估计算法。
  • While it ' s always possible to estimate robust standard errors for ols estimates , if we know something about the specific form of the heteroskedasticity , we can transform the model into one that has homoskedastic errors ? called weighted least squares
    对ols估计稳健标准差总是可能办到的,但是,如果我们知道一些关于异方差结构的信息,我们可以将原模型转化为具有同方差的新模型,这称为加权最小二乘法
  • The tsf method combines efficiently llsf and tri - cubic spline interpolation , learns from others " strong points to offset one ' s weaknesses , so has rapidity and high accuracy of computation and is suitable for contour surface drawing in real - time . 3
    该方法综合多元样条拟合法与局部加权最小二乘法,扬长避短,不仅保证了逼近精度,提高了计算速度,而且加密计算的结果可直接应用于等位面的实时显示。
  • The paper employs the same method that has been used by schwert ( 1989 ) in the examination of the relationship between stock market volatility and macroeconomic volatility . firstly , the paper uses the iterated weighted least squares to estimate the conditional volatilities of economic variables . and then it seasonally adjusts the conditional volatilities on the basis of schwert ( 1989 ) , because according to the analysis of the paper , the conditional volatility of each variable exhibits the cyclical seasonal movements and removing the cyclical seasonal movements will ensure the removal of the effects of nonessential factors on economic variables
    文章依照schwert ( 1989 )检验美国股票市场收益率波动与宏观经济波动之间关系的研究方法通过迭代加权最小二乘法( iteratedwls ) ,首先估计经济变量的条件波动率,并在schwert ( 1989 )的基础上对所求得的条件波动率进行季节调整,文章分析每个经济变量的条件波动率都存在明显的季节性周期运动,消除季节因素即消除了非宏观基本面因素对经济变量的影响。
  • Fifth , through statistical analysis of electrical connector accelerated life test data , verified that the reliability statistical model of electrical connector and the reliability statistical method under doof data are both correct . applied the maximum likelihood estimate method with the least squares estimator of test data as preliminary estimate and weighted least square estimate method separate to treat the different kind test data , obtained the estimator of electrical connector reliability characteristic values
    第五,采用极大似然估计法和加权最小二乘法对电连接器加速寿命试验数据进行了统计分析,得到了电连接器可靠性特征量的估计值,验证了电连接器可靠性统计模型和doof数据下可靠性分析方法的正确性。
  • Firstly , we estimate the variance and the mean of each cell with maximum likelihood ; secondly , we identify the important dispersion effects based on least squares analysis of the logarithm of within - replication variance ; last , we identify the important location effects based on weighted least squares analysis of the mean of each cell . a simulation study also demonstrates its superiority over some existing methods . an experiment for the robust design of thermostat is used to illustrate the method
    本文对带有右截尾数据的有重复因子试验,提出了另一种分析位置效应和散度效应的方法:首先,在每一个试验点,对重复试验观察值用极大似然法估计出均值和方差;其次,用每个试验点方差估计值的对数作为响应变量与各因子建立回归模型,鉴别出显著的散度效应;之后,采用加权最小二乘法鉴别出比较显著的位置效应。
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