Distributed Risk Aversion Parameter Estimation for First-Price Auction in Sensor Networks

Following the Internet, the Internet of Things (IoT) becomes a prime vehicle for supporting auction. The use of market mechanisms to solve computer science problems is gaining significant traction. More and more clues show that the bidders tend to be risk-averse ones. However, traditional nonparamet...

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Bibliographic Details
Published in:International journal of distributed sensor networks 2013-01, Vol.2013 (-), p.1-9
Main Authors: An, Xin, Xu, Shuo, Chen, Jiancheng, Zhang, Yuan
Format: Article
Language:English
Subjects:
Auctions
Computer simulation
Economic models
Engineering research
Estimators
Internet
Internet of things
Markets
Methods
Networks
Real time systems
Risk
Risk aversion
Sensors
Traction
Wireless sensor networks
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Summary:Following the Internet, the Internet of Things (IoT) becomes a prime vehicle for supporting auction. The use of market mechanisms to solve computer science problems is gaining significant traction. More and more clues show that the bidders tend to be risk-averse ones. However, traditional nonparametric approach is only applicable for the case of risk neutrality in a centralized server. This study proposes a generalized nonparametric structural estimation procedure for the first-price auctions in the distributed sensor networks. To evaluate the performance of the aggregated parameter estimators, extensive Monte Carlo simulation experiments are conducted for ten different values of risk aversion parameters including the risk neutrality case in multiple classic scenes. Moreover, in order to improve the usability of the aggregated parameter estimators, some guidance is also given for real-world applications.
ISSN:1550-1329
1550-1477
1550-1477
DOI:10.1155/2013/795630