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JSS Research Series in Statistics
cover

Consistency of an Information Criterion for High-Dimensional Multivariate Regression

Authors: Yanagihara, Hirokazu

  • Reevaluates the consistency of an information criterion by the high-dimensional asymptotic framework 
  • Deals with the high-dimensional asymptotic theory when the normality assumption is violated
  • Considers a wide class of information criteria
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eBook $39.99
price for USA (gross)
  • The eBook version of this title will be available soon
  • Due: November 19, 2020
  • ISBN 978-4-431-55775-3
  • Digitally watermarked, DRM-free
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Softcover $54.99
price for USA
  • Customers within the U.S. and Canada please contact Customer Service at +1-800-777-4643, Latin America please contact us at +1-212-460-1500 (24 hours a day, 7 days a week). Pre-ordered printed titles are excluded from promotions.
  • Due: October 22, 2020
  • ISBN 978-4-431-55774-6
  • Free shipping for individuals worldwide
About this book

This is the first book on an evaluation of (weak) consistency of an information criterion for variable selection in high-dimensional multivariate linear regression models by using the high-dimensional asymptotic framework. It is an asymptotic framework such that the sample size n and the dimension of response variables vector p are approaching ∞ simultaneously under a condition that p/n goes to a constant included in [0,1).Most statistical textbooks evaluate consistency of an information criterion by using the large-sample asymptotic framework such that n goes to ∞ under the fixed p. The evaluation of consistency of an information criterion from the high-dimensional asymptotic framework provides new knowledge to us, e.g., Akaike's information criterion (AIC) sometimes becomes consistent under the high-dimensional asymptotic framework although it never has a consistency under the large-sample asymptotic framework; and Bayesian information criterion (BIC) sometimes becomes inconsistent under the high-dimensional asymptotic framework although it is always consistent under the large-sample asymptotic framework. The knowledge may help to choose an information criterion to be used for high-dimensional data analysis, which has been attracting the attention of many researchers.

Buy this book

eBook $39.99
price for USA (gross)
  • The eBook version of this title will be available soon
  • Due: November 19, 2020
  • ISBN 978-4-431-55775-3
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Softcover $54.99
price for USA
  • Customers within the U.S. and Canada please contact Customer Service at +1-800-777-4643, Latin America please contact us at +1-212-460-1500 (24 hours a day, 7 days a week). Pre-ordered printed titles are excluded from promotions.
  • Due: October 22, 2020
  • ISBN 978-4-431-55774-6
  • Free shipping for individuals worldwide

Bibliographic Information

Bibliographic Information
Book Title
Consistency of an Information Criterion for High-Dimensional Multivariate Regression
Authors
Series Title
JSS Research Series in Statistics
Copyright
2021
Publisher
Springer Japan
Copyright Holder
The Author(s), under exclusive licence to Springer Japan KK
eBook ISBN
978-4-431-55775-3
Softcover ISBN
978-4-431-55774-6
Series ISSN
2364-0057
Edition Number
1
Number of Pages
X, 60
Topics