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lwpr.rar
- 局部线性回归方法及其稳健形式已经被看作一种有效的非参数光滑方法.与流行的核回归方法相比,它有诸多优点,诸如:较高的渐近效率和较强的适应设计能力.另外,局部线性回归能适应几乎所有的回归设计情形却不需要任何边界修正。,Local linear regression methods and their solid form has been seen as an effective non-parametric smoothing method. Contrary to popular kernel
45095smoothing
- 这个帖子中我想讨论的是移动窗口多项式最小二乘拟和平滑方法，粗糙惩罚方法，以及kernel平滑方法。-Posts in this discussion I think are moving window least squares polynomial fitting smoothing method, crude methods of punishment, as well as the kernel smoothing method.
ARMASA_1_9
- Features a unique program to estimate the power spectral density. The spectrum containing all significant details is calculated from a time series model. Model type as well as model order are determined automatically from the data, using statistical
two-smooth-model-forecast
- 二次指数平滑预测模型，采用MATLAB仿真实现，无错误-Second exponential smoothing prediction model using MATLAB Simulation, no error
Quadratic-Exponential-Smoothing
- matlab例子，用二次指数平滑法预测并绘制散点图，附有说明- matlab example, with secondary exponential smoothing forecast and draw a scatter plot