Linear Models and the Relevant Distributions and Matrix Algebra Hardback
by David A. Harville
Part of the Chapman & Hall/CRC Texts in Statistical Science series
Hardback
Description
Linear Models and the Relevant Distributions and Matrix Algebra provides in-depth and detailed coverage of the use of linear statistical models as a basis for parametric and predictive inference.
It can be a valuable reference, a primary or secondary text in a graduate-level course on linear models, or a resource used (in a course on mathematical statistics) to illustrate various theoretical concepts in the context of a relatively complex setting of great practical importance. Features:Provides coverage of matrix algebra that is extensive and relatively self-contained and does so in a meaningful contextProvides thorough coverage of the relevant statistical distributions, including spherically and elliptically symmetric distributionsIncludes extensive coverage of multiple-comparison procedures (and of simultaneous confidence intervals), including procedures for controlling the k-FWER and the FDRProvides thorough coverage (complete with detailed and highly accessible proofs) of results on the properties of various linear-model procedures, including those of least squares estimators and those of the F test. Features the use of real data sets for illustrative purposesIncludes many exercises
Information
-
Out of stock
- Format:Hardback
- Pages:524 pages
- Publisher:Taylor & Francis Ltd
- Publication Date:13/03/2018
- Category:
- ISBN:9781138578333
Other Formats
- Hardback from £91.45
- Paperback / softback from £36.59
- EPUB from £35.99
- PDF from £35.99
Information
-
Out of stock
- Format:Hardback
- Pages:524 pages
- Publisher:Taylor & Francis Ltd
- Publication Date:13/03/2018
- Category:
- ISBN:9781138578333
