Abstract
Much of classical statistical inference for linear models is based on special cases of those models for which the response vector y has a multivariate normal distribution. Before we can present those inferential methods, therefore, we must first precisely define the multivariate normal distribution and the related noncentral chi-square, t, and F distributions, and describe some of their important properties. These are the topics of this chapter. It is possible to extend some of the results presented in this chapter and in the remainder of the book to linear models in which y has a distribution from the more general family of “elliptical” distributions, but we do not consider these extensions here. The reader who is interested in such extensions is referred to Ravishanker and Dey (A first course in linear model theory. Chapman & Hall/CRC Press, Boca Raton, 2002) and Harville (Linear models and the relevant distributions and matrix algebra. CRC Press, Boca Raton, 2018).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
This is an event of probability 0, however.
- 2.
Interchanging integration and summation can be justified by the dominated convergence theorem.
References
Casella, G. & Berger, R. L. (2002). Statistical inference (2nd ed.). Pacific Grove, CA: Duxbury.
Chung, K. L. (1974). A course in probability theory. New York: Academic Press.
Harville, D. A. (1997). Matrix algebra from a statistician’s perspective. New York: Springer.
Harville, D. A. (2018). Linear models and the relevant distributions and matrix algebra. Boca Raton, FL: CRC Press.
Hogg, R. V., McKean, J., & Craig, A. T. (2013). Introduction to mathematical statistics (7th ed.). Boston: Pearson.
Melnick, E. L. & Tenenbein, A. (1982). Misspecifications of the normal distribution. The American Statistician, 36, 372–373.
Ravishanker, N. & Dey, D. K. (2002). A first course in linear model theory. Boca Raton, FL: Chapman & Hall/CRC Press.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Zimmerman, D.L. (2020). Distribution Theory. In: Linear Model Theory. Springer, Cham. https://doi.org/10.1007/978-3-030-52063-2_14
Download citation
DOI: https://doi.org/10.1007/978-3-030-52063-2_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-52062-5
Online ISBN: 978-3-030-52063-2
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)