The weighted kernel estimators of nonparametricregression function with censored data 截尾数据非参数回归函数加权核估计
Establishes of model of quasi - parabola regressive function model and parametric estimation 伪抛物线回归函数模型的建立与参数估计
Exponential bounds of mean error for the kernel regreeion estimates with directional data 方向数据回归函数核估计平均偏差的指数界
Weighted kernel estimator of nonparametric regression functions with censored data of sequences 相依截尾数据非参数回归函数加权核估计
Convergence rate of the estimate of the regression function under martingale difference sequence 误差为鞅差序列的回归函数估计的收敛速度
Estimators of penalized least square for parametric regression and vectors and spline function can be got by compiled program 模拟计算表明,该方法适合于回归函数模型误差与测量系统误差的估计。
In this paper , we discuss the estimate of regression function in nonparametric regression model based on exponential integral martingale difference 摘要本文研究了误差项是鞅差序列,且满足某种指数矩条件的非参数回归函数的估计。
The essence of the above estimating methods is local estimator or local smoothing technique . in general , the non - parametric regression function is . well estimated by the above methods when the covariable x is one dimension 这些方法本质上讲都是局部估计或局部光滑,当回归变量x为一维变量时,非参数回归函数用这些方法一般都能得到很好的估计。
In the nonparametric regression the regression function is supposed to be from some function family , such as the smoothing functions . so the nonparametric regression needs few hypotheses and is very robust 非参数回归一般假定回归函数属于某一个函数类,如常常假定回归函数是一个光滑的函数,因此非参数回归对模型的假设很少,最主要的优点就是模型具有稳健性。
Satisfactory results were obtained . by combining the traditional neural network method with the svr theory , this paper also addresses the problem of boundary value problems and replaces the neural network function with svr regression function 此外,在本课题中,我们把传统的神经网络解边值问题的方法和svr理论相结合,用svr中的回归函数代替神经网络函数,对边值问题的求解进行了研究。