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On superlevel sets of conditional densities and multivariate quantile regression

条件密度超水平集与多元分位数回归

Some common proposals of multivariate quantiles do not sufficiently control the probability content, while others do not always accurately reflect the concentration of probability mass. We suggest superlevel sets of conditional multivariate densities as an alternative to current multivariate quantile definitions. Hence, the superlevel set is a function of conditioning variables much like in quantile regression. We show that conditional superlevel sets have favorable…

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A RANK‐ORDERED LOGIT MODEL WITH UNOBSERVED HETEROGENEITY IN RANKING CAPABILITIES

考虑排序能力不可观测异质性的排序 Logit 模型

Abstract To study preferences, respondents to a survey are usually asked to select their most preferred option from a set. Preferences can be estimated more efficiently if respondents are asked to rank all alternatives. When some respondents are unable to perform the ranking task, using the complete ranking may lead to a substantial bias. We introduce a model which endogenously describes the ranking capabilities of individuals. Estimated preferences based on this model are…

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Modeling category‐level purchase timing with brand‐level marketing variables

利用品牌层面营销变量建模品类层面的购买时点

Abstract Purchase timing of households is usually modeled at the category level. However, many potential explanatory variables are observed at the brand level. To explain interpurchase times one has to either construct category‐level measures of marketing efforts, or integrate the model with a model for brand choice. In this paper we pursue the latter where we use latent brand preferences to capture the relevance of the marketing mix of an individual brand. We compare our…

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