Karl-Rudolf Koch

Parameter Estimation and Hypothesis Testing in Linear Models (eBook, PDF)

• Format: PDF

Produktbeschreibung

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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Produktdetails

• Verlag: Springer Berlin Heidelberg
• Seitenzahl: 334
• Erscheinungstermin: 9. März 2013
• Englisch
• ISBN-13: 9783662039762
• Artikelnr.: 53134766

Inhaltsangabe

1 Vector and Matrix Algebra.- 2 Probability Theory.- 3 Parameter Estimation in Linear Models.- 4 Hypothesis Testing, Interval Estimation and Test for Outliers.- References.