A First Step toward a Unified Theory of Richly Parameterized
Linear Models
Using mixed linear models to analyze data often leads to results
that are mysterious, inconvenient, or wrong. Further compounding
the problem, statisticians lack a cohesive resource to acquire a
systematic, theory-based understanding of models with random
effects.
Richly Parameterized Linear Models: Additive, Time Series, and
Spatial Models Using Random Effects takes a first step in
developing a full theory of richly parameterized models, which
would allow statisticians to better understand their analysis
results. The author examines what is known "and" unknown about
mixed linear models and identifies research opportunities.
The first two parts of the book cover an existing syntax for
unifying models with random effects. The text explains how richly
parameterized models can be expressed as mixed linear models and
analyzed using conventional and Bayesian methods.
In the last two parts, the author discusses oddities that can
arise when analyzing data using these models. He presents ways to
detect problems and, when possible, shows how to mitigate or avoid
them. The book adapts ideas from linear model theory and then goes
beyond that theory by examining the information in the data about
the mixed linear model s covariance matrices.
Each chapter ends with two sets of exercises. Conventional
problems encourage readers to practice with the algebraic methods
and open questions motivate readers to research further. Supporting
materials, including datasets for most of the examples analyzed,
are available on the author s website."
General
Imprint: |
Taylor & Francis
|
Country of origin: |
United States |
Series: |
Chapman & Hall/CRC Texts in Statistical Science |
Release date: |
November 2013 |
First published: |
2014 |
Authors: |
James S Hodges
|
Dimensions: |
234 x 156 x 26mm (L x W x T) |
Format: |
Hardcover
|
Pages: |
470 |
ISBN-13: |
978-1-4398-6683-2 |
Categories: |
Books >
Science & Mathematics >
Mathematics >
Probability & statistics
|
LSN: |
1-4398-6683-X |
Barcode: |
9781439866832 |
Is the information for this product incomplete, wrong or inappropriate?
Let us know about it.
Does this product have an incorrect or missing image?
Send us a new image.
Is this product missing categories?
Add more categories.
Review This Product
No reviews yet - be the first to create one!