Perspectives on Bayesian Methods and Big Data

被引:0
|
作者
Greg M. Allenby
Eric T. Bradlow
Edward I. George
John Liechty
Robert E. McCulloch
机构
[1] Fisher College of Business,The Wharton School
[2] The Ohio State University,Smeal College of Business
[3] University of Pennsylvania,Booth School of Business
[4] The Pennsylvania State University,undefined
[5] University of Chicago,undefined
关键词
Bayesian statistics; Big Data; Scalable computation;
D O I
10.1007/s40547-014-0017-9
中图分类号
学科分类号
摘要
Researchers and practitioners are facing a world with ever-increasing amounts of data and analytic tools, such as Bayesian inference algorithms, must be improved to keep pace with technology. Bayesian methods have brought substantial benefits to the discipline of Marketing Analytics, but there are inherent computational challenges with scaling them to Big Data. Several strategies with specific examples using additive regression trees and variable selection are discussed. In addition, the important observation is made that there are limits to the type of questions that can be answered using most of the Big Data available today.
引用
收藏
页码:169 / 175
页数:6
相关论文
共 50 条
  • [41] Hyperparameter Tuning for Big Data using Bayesian Optimisation
    Joy, Tinu Theckel
    Rana, Santu
    Gupta, Sunil
    Venkatesh, Svetha
    2016 23RD INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR), 2016, : 2574 - 2579
  • [42] A Bayesian perspective of statistical machine learning for big data
    Rajiv Sambasivan
    Sourish Das
    Sujit K. Sahu
    Computational Statistics, 2020, 35 : 893 - 930
  • [43] Introduction to Big Data Analytics and the Special Issue on Big Data Methods and Applications
    Zheng, Zhiqiang
    JOURNAL OF MANAGEMENT ANALYTICS, 2015, 2 (04) : 281 - 284
  • [44] Patching Methods of the Bayesian Network Data
    Gong Yishan
    Hao Jia
    HIS 2009: 2009 NINTH INTERNATIONAL CONFERENCE ON HYBRID INTELLIGENT SYSTEMS, VOL 1, PROCEEDINGS, 2009, : 138 - +
  • [45] Bayesian Learning Methods for Geotechnical Data
    Yuen, Ka-Veng
    Ching, Jianye
    Phoon, Kok-Kwang
    ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART A-CIVIL ENGINEERING, 2021, 7 (01)
  • [46] Principles of Bayesian Methods in Data Analysis
    Krystek, Michael P.
    MEASUREMENT TECHNOLOGY AND INTELLIGENT INSTRUMENTS IX, 2010, 437 : 3 - 7
  • [47] Bayesian methods for analysing ringing data
    Brooks, SP
    Catchpole, EA
    Morgan, BJT
    Harris, MP
    JOURNAL OF APPLIED STATISTICS, 2002, 29 (1-4) : 187 - 206
  • [48] Bayesian methods in the evaluation of scattering data
    Krappe, HJ
    INTERNATIONAL JOURNAL OF MODERN PHYSICS E-NUCLEAR PHYSICS, 2006, 15 (02) : 354 - 361
  • [49] Big Data and Innovative Research Methods
    Mamo, Yoseph Z.
    INTERNATIONAL JOURNAL OF SPORT COMMUNICATION, 2023, 16 (03) : 352 - 360
  • [50] Big Data, Collaboration and Teaching Methods
    Curtis, Bruce
    INTERNATIONAL JOURNAL OF QUALITATIVE METHODS, 2016, 15 (01):