regression function meaning in English
回归函数
Examples
- This paper studies the nonparametric estimates of general weight function of the nonparametric regression function with fixed design points , when the model error is martingale sequence , and we give the optimal convergence rate under some conditions
摘要当误差为鞅差序列时，研究固定设计点列情形下非参数回归函数一般权函数的非参数估计，并在一些基本条件下给出了估计的一致最优强收敛速度。 - Through linear regression , experiment data is tidied to linear regression function relation . these relations can be extended to common high space . the result indicates that outlet velocity and outlet diameter have obvious effect on air distribution
通过线性回归法将实验数据整理成以工作区平均温度为因变量，以各个影响因素为自变量的一元线性回归函数关系式，这些关系式能够推广到一般的高大空间。 - All kinds of the methods are proposed to estimate the nonparametric regression function , such as the kernel method , the local polynomial estimators , the smoothing spline , the series estimators ( b - spline estimator . fourier series estimator , wavelet series estimator )
对于非参数回归人们提出了许多估计方法，如核估计，局部多项式估计，光滑样条估计，级数估计(傅里叶级数估计，小波级数估计)等。 - But the multivariable nonparametric regression function could not be well estimated by the local estimator because there is o nly a little data in the local fields of the high dimension regression variable x . this phenomenon is said to be " the curse of dimension "
但当回归变量是多维向量时，由于x的局部邻域包含很少的数据，用这些估计方法，很难估计出一般的多元非参数回归函数，人们把这种现象称为‘维数祸根’ ( thecurseofdimension ) 。 - On the other hand , they play an important role in the theories of esfimation for regression function . in this paper , we mainly get the large sample properties for partitioning estiona - tion and modified its estimation . for example , we proved their asymptolic normaity under nuture conditions by means of mortingle theory ; we also get their strong consistency for regression function under censored samples ; and finaly we genearzed the result to dependence sample and have strong consistency for the modified partitioning estimation of regression function
因此本论文研究了回归函数基于分割估计及改良基于分割估计的大样本性质，利用鞅的有关理论，在比较自然的条件下，证明了其渐近正态性；首次构造了截尾样本的回归函数基于分割估计及改良基于分割估计，并证明其强相合性；同时把有关结果推广到相依样本下(如混合) ，获得了改良基于分割估计的强相合性及收敛速度。