When errors is a ar (1) time series, we studied the quasi-likelihood equation for the semiparametric model, and investigated the existence of quasi-maximum likelihood estimators.
在误差为AR(1)时间序列的情形下，给出了半参数回归模型的拟极大似然估计方程，并研究了拟极大似然估计量的存在性。
We develop imputation estimators of mean of responses for semiparametric varying-coefficient model with response variables missing at random.
在响应变量随机缺失时，研究了半参数变系数模型响应变量均值的借补估计。
Objective To relax linear assumption of explanatory variable in classical linear model and explore semiparametric regression model.
目的放宽经典线性模型中的解释变量的线性假定和探讨半参数回归分析模型。
In this paper, we have considered a new class of semiparametric regression model Under some mild conditions we have obtained better uniformly strong convergence rates for the proposed estimators.
本文讨论了一类新的半参数回归模型，在一组比较基本的条件下，得到了估计量的较好的一致强收敛速度。
We change the truncated regression model into the semiparametric regression model.
将截断数据回归模型转化成半参数回归模型。
We propose a general semiparametric variance function model in a random design setting.
介绍具有随机设计的一类半参数方差函数模型。
In this paper, a kind of semiparametric errors-in-variables functional relationship model is studied.
本文研究半参数变量含误差函数关系模型。
In this paper, a kind of semiparametric errors-in-variables functional relationship model is studied.
本文研究半参数变量含误差函数关系模型。
应用推荐