Publications
Detailed Information
Logistic regression in sealed-bid auctions with multiple rounds: Application in Korean court auction
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Cook-Hwan | - |
dc.contributor.author | Chang, Woojin | - |
dc.date.accessioned | 2011-12-01T01:45:30Z | - |
dc.date.available | 2011-12-01T01:45:30Z | - |
dc.date.issued | 2011-04-01 | - |
dc.identifier.citation | EXPERT SYSTEMS WITH APPLICATIONS; Vol.38 4; 3098-3115 | - |
dc.identifier.issn | 0957-4174 | - |
dc.identifier.uri | https://hdl.handle.net/10371/74924 | - |
dc.description.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. | - |
dc.language.iso | en | - |
dc.publisher | PERGAMON-ELSEVIER SCIENCE LTD | - |
dc.subject | Sealed-bid auction | - |
dc.subject | Heterogeneity | - |
dc.subject | Successful bid price | - |
dc.subject | Markov chain Monte Carlo | - |
dc.subject | Bayesian statistics | - |
dc.subject | Multiple rounds | - |
dc.subject | Logistic regression | - |
dc.subject | Korean court auction | - |
dc.title | Logistic regression in sealed-bid auctions with multiple rounds: Application in Korean court auction | - |
dc.type | Article | - |
dc.contributor.AlternativeAuthor | 김국환 | - |
dc.contributor.AlternativeAuthor | 장우진 | - |
dc.identifier.doi | 10.1016/j.eswa.2010.08.102 | - |
dc.citation.journaltitle | EXPERT SYSTEMS WITH APPLICATIONS | - |
dc.description.citedreference | Gelman A, 2008, ANN APPL STAT, V2, P1360, DOI 10.1214/08-AOAS191 | - |
dc.description.citedreference | Loubes JM, 2008, ELECTRON J STAT, V2, P661, DOI 10.1214/07-EJS115 | - |
dc.description.citedreference | Kinney SK, 2007, BIOMETRICS, V63, P690, DOI 10.1111/j.1541-0420.2007.00771.x | - |
dc.description.citedreference | Gelman A, 2006, BAYESIAN ANAL, V1, P515 | - |
dc.description.citedreference | OH K, 2006, KOREAN J FUZZY LOGIC, V16, P172 | - |
dc.description.citedreference | O''''''''Brien SM, 2004, BIOMETRICS, V60, P739 | - |
dc.description.citedreference | Efron B, 2004, ANN STAT, V32, P407 | - |
dc.description.citedreference | YANG CY, 2002, KOREAN J RES REGIONA, V34, P18 | - |
dc.description.citedreference | HASTIE T, 2001, ELEMENTS STAT LEARNI | - |
dc.description.citedreference | Ansari A, 2000, J MARKETING RES, V37, P363 | - |
dc.description.citedreference | SPIEGELHALTER D, 1998, BAYESIAN DEVIANCE EF | - |
dc.description.citedreference | HOBERT J, 1996, J AM STAT ASS, V91 | - |
dc.description.citedreference | ALBERT J, 1993, J AM STAT ASSOC, P669 | - |
dc.description.citedreference | TANNER MA, 1987, J AM STAT ASSOC, V82, P528 | - |
dc.description.citedreference | HARTIGAN JA, 1965, ANN MATH STAT, V36, P1137 | - |
dc.description.citedreference | JEFFREYS H, 1961, THEORY PROBABILITY | - |
dc.description.tc | 0 | - |
dc.identifier.wosid | 000286904600021 | - |
- Appears in Collections:
- Files in This Item:
- There are no files associated with this item.
Item View & Download Count
Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.