Models, Models Everywhere…Model Selection

Scott Pardo ()
Additional contact information
Scott Pardo: Ascensia Diabetes Care, Global Medical & Clinical Affairs

Chapter Chapter 11 in Statistical Analysis of Empirical Data, 2020, pp 121-160 from Springer

Abstract: Abstract There are situations where many potential explanatory variables can be measured, but there is no way to know which of those are actually most helpful in predicting the response. Many methods may be employed to either narrow the field or provide a predictive model when it is very difficult to select or eliminate any regressors.

Keywords: Stepwise regression; Bayesian model averaging; Glmulti; Neural network; Cart; Random forests (search for similar items in EconPapers)
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:978-3-030-43328-4_11

Ordering information: This item can be ordered from
http://www.springer.com/9783030433284

DOI: 10.1007/978-3-030-43328-4_11

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 ().