Hedonic pricing modelling with unstructured predictors: an application to Italian fashion industry

DOI10.1007/s10182-022-00465-5OpenAlexW4311350574MaRDI QIDQ6120618

Federico Crescenzi

Publication date: 21 February 2024

Published in: AStA. Advances in Statistical Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10182-022-00465-5

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

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• Rare Feature Selection in High Dimensions
• The solution path of the generalized lasso
• SLOPE-adaptive variable selection via convex optimization
• Deriving the Pricing Power of Product Features by Mining Consumer Reviews
• The Value of Fast Fashion: Quick Response, Enhanced Design, and Strategic Consumer Behavior
• Square-root lasso: pivotal recovery of sparse signals via conic programming
• Graphical Models, Exponential Families, and Variational Inference
• Averaged gene expressions for regression
• Machine Learning for Text
• 10.1162/jmlr.2003.3.4-5.993

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