查询词典 regression effect

The regression curve and equation were gain by monadic non-linear regression model.

对两者进行一元非线性回归模型分析得到回归曲线和回归方程，进一步了解两者间的相关性，同时作出产果量的预测。

A regression equation for forecasting results was established by the multiple regression of experimental data.

对实验数据的多元回归分析得到了可对不同实验条件所得产品絮凝效果进行预测的回归方程。

Robust estimate and biased estimate of regression coefficients are two kinds of regression model fitting methods for non-optimal data.

回归系数的稳健估计和有偏估计是两种根据非典型数据建立线性回归模型的方法。

In the case with k independent variables, the simple regression and the multiple regression produce identical estimate for x1 only if

在k个自变量的情况下，简单回归和多元回归只有在以下条件下才能得到对x1相同的估计

In this paper, we discuss the estimate of regression function in nonparametric regression model based on exponential in tegral mart in gale 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。

Some troubles emerge when we use regression estimator in such a case:in a continuous survey research,when the prior sample and the present sample are independent and they have different elements,we can not compute the regression coefficient.

作连续调查研究抽样时经常用到回归估计。如果前后两个样本相互独立，并且它们所包含的元素不同，就无法直接计算出回归系数。

In the second part , also under NA assumption, we worked on the consistency of kernel estimator of regression function in the nonparametric regression model Y_i =g+ε_i.

第二部分：我们研究了样本为NA相依的情况下，非参数回归模型Y_i=g+ε_ii=1，2，…，n中，回归函数核估计的强，弱相合性。

In the special case of GLM—normal linear model with classical link function,we compare our methods with existing ones and our methods perform more excellently.Finally,sequential detection of structural changes is studied in nonparametric regression models o Based on Nadaraya-Watson estimator of regression function,we calculate the residual series and construct "residual cumulative sum process" with weight values of kernel estimator of "long-run average density function".

在随机模拟一节中，给出了布朗桥的h-增量过程的"Max-Max"泛函统计量的经验分位数表，并在随机模拟中验证了文中所提"部分和"与"滑动和"方法的有效性，同时在广义线性模型取"典则连接函数"时的特例—正态线性模型场合，与已有方法进行了对比，结果显示文中所提方法表现更优。

Support vector regression algorithm is an application of structural risk minimization principle in function regression.

支持向量机回归算法是结构风险最小化原理在函数回归方面的应用。

The support vector regression model is trained using historical data and the regression function is obtained.

根据历史数据对SVR进行训练，得到回归函数。

It was just a normal day of school

那只是上学的普通一天

Which is a very good reference in this issue.

这是一个在这个问题上很好的参考。