现有平滑技术利用不同的折扣和补偿策略来处理数据稀疏问题，在计算复杂性与合理性方面各有其优缺点。
The present smoothing techniques deal with the data sparse problem using different discount and compensate strategy, and they have different merit or shortcoming on complexity and rationality.
现有平滑技术虽然已有效地对数据稀疏问题进行了处理，但对已出现事件频率分布的合理性并没有作出有效的分析。
The present smoothing techniques have solved the data sparse problem effectively but have not further analyzed the reasonableness for the frequency distribution of events occurring.
本文对交叉证认技术选取平滑因子的若干问题进行了探讨，许采用模拟数据的方式验证了作者的观点。
In this paper, some problems about smoothing factor selected by cross-validation technique are discussed and tested by using the simulation data.
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