Weighted Type Least Squares Based on Different Important Data Point
Yongsheng Cheng · 2006
In traditional Least Squares, all data points are deemed to have the same influence on forecasted point. However, it isn’t the fact. Different data points should have different status. Taking timing serial data for example, recent data points usually have more influence on forecasted point, while forepart data away from expected period have less. So here we bring forward Weighted type Least Squares(WTLS). It gives different weight to different data point in the Q equation. Then the parameters of the equation are estimated. Put forward the mechanism to establishment weights in the method of weighted type Least Squares. Exponential weight is designed to serve timing serial data.