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Parameter Estimation and Hypothesis Testing in Linear Models

Parameter Estimation and Hypothesis Testing in Linear Models

by Karl-Rudolf Koch

Distribution (Probability theory)GeographyEngineering mathematicsPhysical geographyStatistical hypothesis testing
0.0
Open Library
Open Library

About this book

This textbook deals with the estimation of unknown parameters, the testing of hypotheses and the estimation of confidence intervals in linear models. The reader will find 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. To make the book self-contained most of the necessary theorems of vector and matrix algebra and the probability distributions of test statistics are derived. Students of geodesy as well as of the natural sciences and engineering will find the emphasis on the geodetic application of statistical models extremely useful.

Themes & subjects

Distribution (Probability theory)GeographyEngineering mathematicsPhysical geographyStatistical hypothesis testingLinear models (statistics)

Author

Karl-Rudolf Koch

Pages

333

Read time

≈ 8h

Editions

1

Language

English

Publisher

Springer Berlin Heidelberg

ISBN

9783642084614

Where to buy

TR
Amazon Bookshop

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