Richly Parameterized Linear Models - Additive, Time Series, and Spatial Models Using Random Effects

Zusatztext 95152200 Informationen zum Autor James S. Hodges Klappentext This book takes a first step in developing a full theory of richly parameterized models, which would allow statisticians to better understand their analysis results. Zusammenfassung This book takes a first step in developing a full theory of richly parameterized models, which would allow statisticians to better understand their analysis results. Inhaltsverzeichnis Mixed Linear Models: Syntax, Theory, and Methods: An Opinionated Survey of Methods for Mixed Linear Models. Two More Tools: Alternative Formulation, Measures of Complexity. Richly Parameterized Models as Mixed Linear Models: Penalized Splines as Mixed Linear Models. Additive Models and Models with Interactions. Spatial Models as Mixed Linear Models. Time-Series Models as Mixed Linear Models. Two Other Syntaxes for Richly Parameterized Models. From Linear Models to Richly Parameterized Models: Mean Structure: Adapting Diagnostics from Linear Models. Puzzles from Analyzing Real Datasets. A Random Effect Competing with a Fixed Effect. Differential Shrinkage. Competition between Random Effects. Random Effects Old and New. Beyond Linear Models: Variance Structure: Mysterious, Inconvenient, or Wrong Results from Real Datasets. Re-Expressing the Restricted Likelihood: Two-Variance Models. Exploring the Restricted Likelihood for Two-Variance Models. Extending the Re-Expressed Restricted Likelihood. Zero Variance Estimates. Multiple Maxima in the Restricted Likelihood and Posterior.

Product details

• Authors: James S Hodges, James S. Hodges, James S. (University of Minnesota Hodges, Hodges James S.
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Hardback
• Released: 04.11.2013
• EAN: 9781439866832
• ISBN: 978-1-4398-6683-2
• No. of pages: 470
• Series: Chapman & Hall/CRC Texts in Statistical Science; Chapman & Hall/CRC Texts in Statistical Science
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; MATHEMATICS / Probability & Statistics / General, Biology, life sciences, Probability & statistics, Probability and statistics