Method for establishing constrained least square maximum entropy quantile function model
A least squares and function model technology, applied in electrical digital data processing, special data processing applications, instruments, etc., can solve the problems of poor calculation accuracy and low calculation efficiency of the classical maximum entropy quantile value function model, and achieve calculation results. The effect of stable accuracy, high calculation efficiency and high calculation accuracy
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[0037] The present invention will be further described below in conjunction with the drawings and embodiments.
[0038] figure 2 Shown is the quantile function curve fitting process diagram based on the constrained least squares maximum entropy quantile function model, as follows:
[0039] 1) Establish an unconstrained least squares maximum entropy quantile function model
[0040] Set random variable X, u(x)=P(X≤x) is the cumulative distribution function value of X, and satisfy 0≤u(x)≤1, then the unconstrained least squares maximum entropy quantile function of random variable x(u) is:
[0041]
[0042] Where λ ls-qf, j (j=0,1,...,m) is the Lagrangian multiplier, that is, the undetermined coefficient; the number of Lagrangian multipliers is m+1. The cumulative distribution function u(x) and the unconstrained least squares maximum entropy quantile function x(u) are inverse functions to each other.
[0043] The steps to determine the Lagrange multiplier are as follows:
[0044] 11) Re-de...
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