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Dynamically integrated regression model for online auction data

Science China Mathematics 2022年第7期65卷 1531-1552页

作者： Mengying You Huazhen Lin Hua Liang Center of Statistical Research School of StatisticsSouthwestern University of Finance and EconomicsChengdu 611130China Department of Statistics George Washington UniversityWashingtonDC 20052USA

We propose a dynamically integrated regression model to predict the price of online auctions,including the final price.Different from existing models,the proposed method uses not only the historical price but also the information from bidding time.Consequently,the prediction accuracy is improved compared with the existing methods.An estimation method based on B-spline approximation is proposed for the estimation and the inference of parameters and nonparametric functions in this model.The minimax rate of convergence for the prediction risk and large-sample results including the consistency and the asymptotic normality are established.Simulation studies verify the finite sample performance and the appealing prediction accuracy and robustness.Finally,when we apply our method to a 7-day auction of iPhone 6s during December 2015 and March 2016,the proposed method predicts the ending price with a much smaller error than the existing models.

关键词： B-spline dynamic forecasting model functional linear regression model minimax rate online auction

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A selective overview of sparse sufficient dimension reduction

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Statistical Theory and Related Fields 2020年第2期4卷 121-133页

作者： Lu Li Xuerong Meggie Wen Zhou Yu East China Normal University ShanghaiPeople’s Republic of China Missouri University of Science and Technology RollaMOUSA

High-dimensional data analysis has been a challenging issue in statistics.Sufficient dimension reduction aims to reduce the dimension of the predictors by replacing the original predictors with a minimal set of their linear combinations without loss of information.However,the estimated linear combinations generally consist of all of the variables,making it difficult to interpret.To circumvent this difficulty,sparse sufficient dimension reduction methods were proposed to conduct model-free variable selection or screening within the framework of sufficient dimension reduction.Wereview the current literature of sparse sufficient dimension reduction and do some further investigation in this paper.

关键词： minimax rate sparse sufficient dimension reduction variable selection variable screening

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