On the Problem of Model Selection Based on the Data

Kei Takeuchi ()
Additional contact information
Kei Takeuchi: Professor Emeritus, The University of Tokyo

Chapter Chapter 12 in Contributions on Theory of Mathematical Statistics, 2020, pp 329-356 from Springer

Abstract: Abstract The problem of model selection can be discussed in various ways. This chapter deals with the problem from the viewpoint of selection among a class of parametric family the one which can be considered to be the closest approximation of the true model, and it leads to the criterion of AIC.

Date: 2020
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-4-431-55239-0_12

Ordering information: This item can be ordered from
http://www.springer.com/9784431552390

DOI: 10.1007/978-4-431-55239-0_12

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().