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Logistic regression in sealed-bid auctions with multiple rounds: Application in Korean court auction

Cited 1 time in Web of Science Cited 2 time in Scopus
Authors
Kim, Cook-Hwan; Chang, Woojin
Issue Date
2011-04-01
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Citation
EXPERT SYSTEMS WITH APPLICATIONS; Vol.38 4; 3098-3115
Keywords
Sealed-bid auctionHeterogeneitySuccessful bid priceMarkov chain Monte CarloBayesian statisticsMultiple roundsLogistic regressionKorean court auction
Abstract
This paper proposes a forecasting method for court auction information system using logistic regression model with heterogeneity across the multiple round. The goal is to predict whether an individual auction item in a certain round will be sold or not. A simple linear regression and the least angle regression (LARS) containing random effect terms were used to select meaningful variables for our logit model. The link function of the proposed logit model is represented by two bundles of parameters. The former part consists of the parameters whose values do not change over rounds. The latter part has parameters whose values interact with rounds. The observed data corresponding to an appraiser price as well as an intercept term reflecting local characteristics are used without any change. Data that corresponds to all the other parameters is not directly used, but transformed based on similarities between the original item and the surrounding auction items being recommended by the court auction experts. We tested the Bayesian logistic regression by establishing different priors: Dunson''''''''s prior, Gelman''''''''s prior and Ansari''''''''s prior. Dunson''''''''s prior was found to perform the best. Little significant difference was found between the results of the other two priors. These findings indicate that logistic regression taking the heterogeneity of multi-round into account performs better than a one-layered neural network over all time periods. (C) 2010 Elsevier Ltd. All rights reserved.
ISSN
0957-4174
Language
English
URI
https://hdl.handle.net/10371/74924
DOI
https://doi.org/10.1016/j.eswa.2010.08.102
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College of Engineering/Engineering Practice School (공과대학/대학원)Dept. of Industrial Engineering (산업공학과)Journal Papers (저널논문_산업공학과)
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