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在现有的尝试-重购模型的基础上,本文构建了一个更加合理的logit形式的尝试-重购模型。发展出一套适用于该模型的估计方法和检验方法,并用Monte Carlo随机模拟实验对此方法的有效性进行验证。经检验,随着样本数据量的增加和样本标准差的减小,无论是模型参数的估计误差,还是单参数显著性检验的效力,以及犯第一类错误的可能性都表现出合理的变化趋势。该模型可以用于快速消费品新产品的销量预测和营销组合分析。
Based on the existing trial-repo model, this paper constructs a more rational logit-style attempt-repo model. Developed a set of estimation methods and test methods suitable for the model, and verified the validity of the method by Monte Carlo stochastic simulation. It has been tested that with the increase of the sample data amount and the decrease of the standard deviation of the sample, both the estimation error of the model parameter, the validity of the one-parameter significance test and the possibility of making the first type of error all show reasonable changes trend. The model can be used for sales forecasting and marketing mix analysis of new products in FMCG.