| 1. | Too high a degree polynomial produces lower residuals, but at the expense of smoothness in the derivative .
一个很高次数的多项式会产生较低的残差，但却要破坏导数的光滑性。 |
| 2. | In general, experience has shown that third-to fifth-degree polynomials produce sufficiently low residuals and monotonically increasing derivatives .
实践证明，三至五次多项式就能产生足够小的残差和单调递增的导数。 |
| 3. | Then , do a simple regression of y on to obtain
换句话说，是由回归得到的残差。 |
| 4. | A gmres based polynomial preconditioning algorithm
的多项式预处理广义极小残差法 |
| 5. | Properties of ols : minimize the sum of squared residuals
Ols性质：最小化残差平方和。 |
| 6. | There exist positive serial correlation among the residuals
残差之间存在正的序列相关。 |
| 7. | Testing linear regression relationship via trend analysis of residuals
基于残差的趋势性分析检验线性回归关系 |
| 8. | Least - absolute - residuals estimates
最小绝对残差估计 |
| 9. | The error cannot be observed but can be estimated from ols residuals
不可观测的误差可以通过ols残差进行估计。 |
| 10. | Application of residual recognizing model in environmental system prediction
残差辨识模型在环境系统预测中的应用 |
