Multivariate Models

David J. Olive
Additional contact information
David J. Olive: Southern Illinois University, Department of Mathematics

Chapter Chapter 10 in Linear Regression, 2017, pp 299-312 from Springer

Abstract: Abstract The multivariate location and dispersion model is a special case of the multivariate linear regression model when the design matrix is equal to the vector of ones: X = 1. See Chapter 12 (Similarly, the location model is a special case of the multiple linear regression model. See Section 2.9.1 ) The multivariate normal and elliptically contoured distributions are important parametric models for the multivariate location and dispersion model. The multivariate normal distribution is useful in the large sample theory of the linear model, covered in Chapter 11 , while elliptically contoured distributions are useful for multivariate linear regression. Section 3.4.1 used prediction regions for iid multivariate data to bootstrap hypothesis tests.

Keywords: Mahalanobis Distance; Dispersion Model; Multiple Linear Regression Model; Multivariate Normal Distribution; Sample Covariance Matrix (search for similar items in EconPapers)
Date: 2017
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:978-3-319-55252-1_10

Ordering information: This item can be ordered from
http://www.springer.com/9783319552521

DOI: 10.1007/978-3-319-55252-1_10

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 ().