The Linear Model And Hypothesis
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The Linear Model And Hypothesis
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Author : George Seber
language : en
Publisher:
Release Date : 2015
The Linear Model And Hypothesis written by George Seber and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Linear models (Statistics) categories.
This book provides a concise and integrated overview of hypothesis testing in four important subject areas, namely linear and nonlinear models, multivariate analysis, and large sample theory. The approach used is a geometrical one based on the concept of projections and their associated idempotent matrices, thus largely avoiding the need to involve matrix ranks. It is shown that all the hypotheses encountered are either linear or asymptotically linear, and that all the underlying models used are either exactly or asymptotically linear normal models. This equivalence can be used, for example, to extend the concept of orthogonality in the analysis of variance to other models, and to show that the asymptotic equivalence of the likelihood ratio, Wald, and Score (Lagrange Multiplier) hypothesis tests generally applies.
The Linear Hypothesis
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Author : George Arthur Frederick Seber
language : en
Publisher:
Release Date : 1980
The Linear Hypothesis written by George Arthur Frederick Seber and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1980 with Mathematical statistics categories.
Testing Research Hypotheses With The General Linear Model
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Author : Keith A. McNeil
language : en
Publisher: SIU Press
Release Date : 1996
Testing Research Hypotheses With The General Linear Model written by Keith A. McNeil and has been published by SIU Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Mathematics categories.
Briefly describes 777 serial bibliographies relating to modern literature in most of the major languages. Chapters cover comprehensive bibliographies, those for English and foreign literatures, for topics from African American studies to women's studies, and for particular authors. The 1982 edition has been updated and expanded to include information on electronic serial bibliographies. Paper edition (unseen), $19.75. Annotation copyright by Book News, Inc., Portland, OR
Disturbances In The Linear Model Estimation And Hypothesis Testing
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Author : C. Dubbelman
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Disturbances In The Linear Model Estimation And Hypothesis Testing written by C. Dubbelman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Business & Economics categories.
1. 1. The general linear model All econometric research is based on a set of numerical data relating to certain economic quantities, and makes infer ences from the data about the ways in which these quanti ties are related (Malinvaud 1970, p. 3). The linear relation is frequently encountered in applied econometrics. Let y and x denote two economic quantities, then the linear relation between y and x is formalized by: where {31 and {32 are constants. When {31 and {32 are known numbers, the value of y can be calculated for every given value of x. Here y is the dependent variable and x is the explanatory variable. In practical situations {31 and {32 are unknown. We assume that a set of n observations on y and x is available. When plotting the ob served pairs (x l' YI)' (x ' Y2)' . . . , (x , Y n) into a diagram with x 2 n measured along the horizontal axis and y along the vertical axis it rarely occurs that all points lie on a straight line. Generally, no b 1 and b exist such that Yi = b + b x for i = 1,2, . . . ,n. Unless 2 l 2 i the diagram clearly suggests another type of relation, for instance quadratic or exponential, it is customary to adopt linearity in order to keep the analysis as simple as possible.
Parameter Estimation And Hypothesis Testing In Linear Models
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Author : Karl-Rudolf Koch
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09
Parameter Estimation And Hypothesis Testing In Linear Models written by Karl-Rudolf Koch and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Mathematics categories.
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.
Advanced Linear Models
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Author : Shein-Chung Chow
language : en
Publisher: Routledge
Release Date : 2018-05-04
Advanced Linear Models written by Shein-Chung Chow and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-04 with Mathematics categories.
This work details the statistical inference of linear models including parameter estimation, hypothesis testing, confidence intervals, and prediction. The authors discuss the application of statistical theories and methodologies to various linear models such as the linear regression model, the analysis of variance model, the analysis of covariance model, and the variance components model.
Disturbances In The Linear Model Estimation And Hypothesis Testing
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Author : Cornelis Dubbelman
language : en
Publisher:
Release Date : 1978
Disturbances In The Linear Model Estimation And Hypothesis Testing written by Cornelis Dubbelman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1978 with Econometrics categories.
Sample Size Choice
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Author : Robert E. Odeh
language : en
Publisher: CRC Press
Release Date : 2020-08-11
Sample Size Choice written by Robert E. Odeh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-11 with Mathematics categories.
A guide to testing statistical hypotheses for readers familiar with the Neyman-Pearson theory of hypothesis testing including the notion of power, the general linear hypothesis (multiple regression) problem, and the special case of analysis of variance. The second edition (date of first not mentione
Multiple Hypotheses Testing In The Linear Regression Model With Applications To Economics And Finance
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Author : Raimund Alt
language : en
Publisher: Cuvillier Verlag
Release Date : 2005
Multiple Hypotheses Testing In The Linear Regression Model With Applications To Economics And Finance written by Raimund Alt and has been published by Cuvillier Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with categories.
Plane Answers To Complex Questions
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Author : Ronald Christensen
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09
Plane Answers To Complex Questions written by Ronald Christensen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Mathematics categories.
This textbook provides a wide-ranging introduction to the use and theory of linear models for analyzing data. The authors emphasis is on providing a unified treatment of linear models, including analysis of variance models and regression models, based on projections, orthogonality, and other vector space ideas. Every chapter comes with numerous exercises and examples that make it ideal for a graduate- level course. All of the standard topics are covered in depth. In addition, the book covers topics that are not usually treated at this level, but which are important in their own right. The author, Ronald Christensen, is a Professor of Statistics at the University of New Mexico.