The Coordinate-Free Approach to Linear Models (Cambridge Series in Statistical and Probabilistic Mathematics) - ISBN:0521868424

The Coordinate-Free Approach to Linear Models (Cambridge Series in Statistical and Probabilistic Mathematics)

Date: 13 April 2011, 09:38

Free register and download UseNet downloader, then you can FREE Download from UseNet.

Download without Limit " The Coordinate-Free Approach to Linear Models (Cambridge Series in Statistical and Probabilistic Mathematics) " from UseNet for FREE!

Product Description: This book is about the coordinate-free, or geometric, approach to the theory of linear models; more precisely, Model I ANOVA and linear regression models with nonrandom predictors in a finite-dimensional setting. This approach is more insightful, more elegant, more direct, and simpler than the more common matrix approach to linear regression, analysis of variance, and analysis of covariance models in statistics. The book discusses the intuition behind and optimal properties of various methods of estimating and testing hypotheses about unknown parameters in the models. Topics covered include inner product spaces, orthogonal projections, book orthogonal spaces, Tjur experimental designs, basic distribution theory, the geometric version of the Gauss-Markov theorem, optimal and nonoptimal properties of Gauss-Markov, Bayes, and shrinkage estimators under the assumption of normality, the optimal properties of F-tests, and the analysis of covariance and missing observations.

Download Links:

Download Link (High Speed Download)

Download Link (http://www.filesonic.com/...T)

DISCLAIMER:

This site does not store The Coordinate-Free Approach to Linear Models (Cambridge Series in Statistical and Probabilistic Mathematics) on its server. We only index and link to The Coordinate-Free Approach to Linear Models (Cambridge Series in Statistical and Probabilistic Mathematics) provided by other sites. Please contact the content providers to delete The Coordinate-Free Approach to Linear Models (Cambridge Series in Statistical and Probabilistic Mathematics) if any and email us, we'll remove relevant links or contents immediately.