线性假设 meaning in Chinese
linear hypothesis
Examples
- Conclusion it demands no assumption of linearity and is a powerful tool that can flexibly explores the non - linear relationship between independent variable and dependent variable
结论广义加性模型不需要对模型的线性假设，应用起来灵活性强，是探索变量间复杂关系的有力工具。 - However , two - stage estimates of regression coefficients corresponding to these two estimates have approximate equal mean square error . for testing linear hypothesis about regression coefficients , banerjee and magnus ( 1997 ) studied the sensitivity of f - test sta , tistic ( fgls ( ) ) based on generalized least square estimate caused by variance parameter in general case and proposed sensitivity statistic and its distribution
关于回归系数的线性假设检验问题， banerjee和magnus ( 1997 )在一般情况下从理论上研究了方差参数对基于广义最小二乘估计的f -检验统计量( f _ ( gls ) ( ) )的种种影响，提出了敏感性的概念，并给出敏感统计量的形式及其分布。 - ( 3 ) how to design the bayesian test method about the parameter ' s linear hypothesis according to the relationship between the multivariate t distribution and f distribution . ( 4 ) the bayesian diagnosis and unit root test method about the random error series . ( 5 ) the bayesian mean value quality control chart when the variance is known and the mean value - standard error control chart when the variance is unknown
然后，研究了扩散先验分布下单方程模型参数的贝叶斯估计理论，证明了模型系数的后验分布为多元t分布，模型误差项方差的后验估计为逆gamma分布；根据多元t分布和f分布之间的关系，构造了模型系数线性假设检验的贝叶斯方法；根据hpd置信区间构造了随机误差序列自相关的贝叶斯诊断和单位根检验方法，并利用单方程模型的贝叶斯推断理论研究了方差已知时的贝叶斯均值控制图和方差未知时的贝叶斯均值?标准差控制图。 - Anderson , amemiva and fujisawa et al scholars extended the growth curve model into the one with random effects and considered the likelihood ratio criterion ( lrc ) for its mean structure , where the random vectors follow normal distribution on the assumptions that random effects and random errors are mutually independent [ 1 ] [ 2 ]
Anderson ， amemiva和fujisawa等学者将gc模型推广为含有随机效应的增长曲线模型( thegrowthcurvemodelwithrandomeffects ) ，并在观察矩阵服从正态分布的条件下作了关于均值的广义线性假设似然比检验。