We also propose a general method for controlling multiple-group false selection rates, which we apply to second-order linear regression models. By estimating a separate entry level for first-order and second-order terms, we obtain equal contributions to the false selection rate from each group. ...
In this paper,the auther obtains some inequalities of the risk of the OLS estimator ,the GLS estimator and the RGLS estimator under quadratic loss and Fisher s loss in seemingly unrelated regression model. 本文给出了相依回归模型的OLS估计,GLS估计和RGLS估计在二次损失和Fisher损失下的风险估计不等...
5) quadratic regression model 二阶回归模型 1. A mobility model was proposed,which establishes thequadratic regression modelof mobility based on the density differences in compact perio. 本文研制了γ射线床层密度在线探测器,实现了跳汰机床层内沿垂直方向上三点处的床层密度测量,在此基础上,通过记录跳汰机...
6) second order autoregressive model 二阶自回归相依模型补充资料:自回归 自回归 auto - regression 自回归【auto一比g,551.;a.:operpece,,〕 给定随机序列{戈、;n一0,土1】}中的值戈与其先行值弋l…‘戈,的回归依赖关系m阶线性自回U刁由X。与刃二一*(天=l…,m)之间的线性回归(regresslon)方程...
Second-order model with 1 independent variable,即同一个item不同的变量,比如都是x1: Interaction model with 2 independent variables 综合以上线性项,高次项及交互项,将它们相互搭配: 最好使用backward方法,即将所有可能放入模型,比如高次项或高次项,如果没有则会扔掉。二次通常都保留了,但是三次项不考虑。二...
In this paper, the methods for modeling the slump flow of concrete using second-order regression and artificial neural network (ANN) are described. This study led to the following conclusions: (1) The slump flow model based on ANN is much more accurate than that based on regression analysis....
is taken as the design criterion. Optimal designs under this criterion are derived, via a combination of algebraic and numerical techniques, for the full second-order regression model over cuboidal regions. Use of a convexity argument and a surrogate objective function significantly reduces the computa...
Second Order Asymptotic Risks of Smoothed Linear Estimators in Nonparametric Regression Modelsdoi:10.1080/02331889208802371We consider experiments with fixed design points and replicated observations at these points, and investigate smoothed linear estimators of the mean vector of these observations. We propose...
We study a fundamental class of regression models called the second order linear model (SLM). The SLM extends the linear model to high order functional space and has attracted considerable research interest recently. Yet how to efficiently learn the SLM under full generality using nonconvex solver...
To this end, we extend the existing zero-order point estimation to higher orders of regression, allowing us to approximate a mapping function between local LR-HR image patches by a polynomial function. Extensive experiments on open-access MR image datasets and actual clinical MR images demonstrate...