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Parameter Estimation and Hypothesis Testing in Linear Models

Download or Read eBook Parameter Estimation and Hypothesis Testing in Linear Models PDF written by Karl-Rudolf Koch and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 344 pages. Available in PDF, EPUB and Kindle.
Parameter Estimation and Hypothesis Testing in Linear Models
Author :
Publisher : Springer Science & Business Media
Total Pages : 344
Release :
ISBN-10 : 9783662039762
ISBN-13 : 3662039761
Rating : 4/5 (62 Downloads)

Book Synopsis Parameter Estimation and Hypothesis Testing in Linear Models by : Karl-Rudolf Koch

Book excerpt: A treatment of estimating unknown parameters, testing hypotheses and estimating confidence intervals in linear models. Readers will find here presentations of the Gauss-Markoff model, the analysis of variance, the multivariate model, the model with unknown variance and covariance components and the regression model as well as the mixed model for estimating random parameters. A chapter on the robust estimation of parameters and several examples have been added to this second edition. The necessary theorems of vector and matrix algebra and the probability distributions of test statistics are derived so as to make this book self-contained. Geodesy students as well as those in the natural sciences and engineering will find the emphasis on the geodetic application of statistical models extremely useful.


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