Summary and Info
''This book covers a wide range of statistical models, including hierarchical, hierarchical generalized linear, linear mixed, dynamic linear, smoothing, spatial, and longitudinal. It presents a framework for expressing these richly parameterized models together as well as tools for exploring and interpreting the results of fitting the models to data. It extends the standard theory of linear models and illustrates the advantages and disadvantages of various theories. The book also examines surprising or undesirable results arising in the use of the models to analyze real data sets from collaborative research''-- Read more...
More About the Author
James Leonard Hodges (April 24, 1790 – March 8, 1846) was a U.S. Representative from Massachusetts.
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Richly Parameterized Linear Models: Additive, Time Series, and Spatial Models Using Random Effects 0 out of 5 stars based on 0 ratings.