@ARTICLE{AXCZ13,

 author = {An, Xin and Xu, Shuo and Chen, Jiancheng and Zhang, Yuan},

 title = {Distributed Risk Aversion Parameter Estimation for First-Price Auction

in Sensor Networks},

 journal = {International Journal of Distributed Sensor Networks},

 year = {2013},

 volume = {2013},

 pages = {1--9},

 abstract = {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 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.},

 doi = {10.1155/2013/795630},

 keywords = {Risk Aversion Parameter Estimation sep First-Price Auction sep Distributed

Sensor Networks sep Monte Carlo Simulation sep Non-parametric Method},

}

全文：AXCZ13.pdf