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Least squares approximation to lognormal sum distribution via piecewise linear functions

机译:通过分段线性函数对对数正态分布的最小二乘近似

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In this paper, the least squares approximation via a piecewise linear function approach is applied to solve the approximation problem of a sum of lognormal random variables. A number of linear basis functions are applied and the corresponding coefficients are specified to form a piecewise linear approximation to the sum lognormal cumulative distribution function. By using the proposed approach, arbitrary precision of the approximation can be achieved by increasing the number of basis functions. The computation complexity shows no significant increase with the increase of the number of basis functions. Simulation results exhibit a desirable performance by using the proposed approximation method through piecewise linear basis functions.
机译:在本文中,通过分段线性函数方法的最小二乘近似被用于解决对数正态随机变量之和的近似问题。应用了许多线性基函数,并指定了相应的系数,以形成与和对数正态累积分布函数的分段线性近似。通过使用所提出的方法,可以通过增加基函数的数量来实现近似的任意精度。随着基本函数数量的增加,计算复杂度没有显着增加。通过使用分段线性基函数的拟议近似方法,仿真结果显示出理想的性能。

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