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实际工作中观测到的数据通常是离散和有限的,往往需要构造其函数形式,数据拟合是离散数据连续化的重要方法,而基函数的选择将对拟合效果的好坏起到至关重要的作用。本文主要选取两种基函数模型:傅里叶基函数和B样条基函数,并将其应用到期货市场上棉花的月平均价格指数的拟合分析中。研究结果表明:棉花期货的价格指数变化并无明显周期性,而B样条基能够较好地拟合非周期性数据。
The data observed in practical work is usually discrete and limited, often need to construct its function form. Data fitting is an important method of continuous data discretization, and the choice of basis function will be good for the fitting effect. Important role. In this paper, we mainly select two kinds of basis function models: the Fourier basis function and the B-spline basis function, and apply them to the fitting analysis of the monthly average price index of cotton on the futures market. The results show that there is no obvious periodicity in the price index of cotton futures, and the B-spline can fit the non-periodic data well.