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作物保险纯费率的精确厘定依赖于单产分布的正确选择。把非参数分布作为先验分布,同时考虑影响单产分布的矩信息,应用最小叉熵优化模型得到最小叉熵分布,基于最小叉熵分布厘定作物保险纯费率,实现非参数纯费率的调整。把这种方法应用到辽宁四种主要作物上,进行实证分析,得到结论:调整后的费率比未调整的非参数费率都低,解决了非参数费率偏高的问题。最小叉熵分布同时考虑了先验分布和更多关于分布的矩信息,是更合理的作物单产分布,改进了作物保险纯费率厘定的方法,提高了计算结果的合理性与准确性,可以为保险实践提供更有价值的参考。
The exact determination of the net rate of crop insurance depends on the correct choice of yield distribution. Taking the nonparametric distribution as the prior distribution and considering the moment information affecting the yield distribution, the minimum cross-entropy distribution is obtained by using the minimum cross-entropy optimization model. The pure crop insurance premium rate is determined based on the minimum cross-entropy distribution and the nonparametric pure rate adjustment . Applying this method to four main crops in Liaoning Province, the empirical analysis shows that the adjusted rate is lower than the non-adjusted nonparametric rate and solves the problem of high nonparametric rate. The minimum fork entropy distribution considers both the prior distribution and more information about the distribution of moments, which is a more reasonable distribution of crop yield, improves the method of determining the pure rate of crop insurance, improves the rationality and accuracy of the calculation results, Provide more valuable reference for insurance practice.