基于纵向数据半参数混合效应模型的网络营销影响因素研究
Research on the Influencing Factors of Online Marketing Based on Longitudinal Data Semi Parametric Mixed Effects Model
摘要: 本文建立了一个纵向数据的半参数混合效应模型，采用B样条方法建立纵向指标与时间的关系，为模型中的所有未知参数和随机效应指定先验分布，在共轭先验条件下，对该模型进行贝叶斯分析，通过Gibbs抽样方法获取未知参数、随机效应和非参数函数的贝叶斯估计。最后将该模型应用于饮食类非遗产品网络营销的影响因素进行分析，实证结果显示本文建立的指标对淘宝店铺的网络销售量产生了不同程度的影响，证明了模型的有效性。
Abstract: This article establishes a semi parametric mixed effects model for longitudinal data, using the B-spline method to establish the relationship between longitudinal indicators and time. Prior distributions are specified for all unknown parameters and random effects in the model, and Bayesian analysis of the model is considered under conjugate priors. Bayesian estimates of unknown parameters, random effects, and non parametric functions are extracted based on Gibbs sampling, and the model is applied to the study of influencing factors in online marketing. The empirical results show that the indicators established in this article have varying degrees of impact on the online sales volume of Taobao stores, proving the effectiveness of the model.
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