基于copula的多种关联直接效用方法

D. Jun, Chul Kim
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引用次数: 0

摘要

直接效用方法可以处理多个离散/连续选择结果。然而,在允许两种选择的未观察到的感知质量之间的相关性和计算负担之间存在权衡。如果我们允许相关性,那么我们就必须做数值积分来得到可能性,而如果我们放弃相关性,那么我们就可以得到封闭形式的可能性。因此,我们提出了一种新的基于copula的直接效用方法,它不仅允许相关性,而且提供了似然的封闭形式。从经验上,我们发现两种选择的未观察到的品质之间存在相关性。忽略这种相关性可能会导致对共同购买的误解。
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A Copula-Based Direct Utility Approach with Various Correlations
A direct utility approach can handle multiple discrete/continuous choice outcomes. However, there is a trade-off between allowing correlations between unobserved perceived qualities of two alternatives and computational burden. If we allow the correlations, then we have to do numerical integrations for getting likelihoods, whereas if we give up the correlations, then we can get closed form likelihood. Thus, we suggest a new copula-based direct utility approach that not only allows the correlations but also provides closed form of likelihood. Empirically, we find the existence of the correlations between unobserved qualities of two alternatives. Ignoring the correlations may cause the misunderstanding of the joint-purchases.
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