Plane Answers to Complex Questions [recurso electrónico] : The Theory of Linear Models / by Ronald Christensen.

Por: Christensen, Ronald [author.]Colaborador(es): SpringerLink (Online service)Tipo de material: TextoTextoSeries Springer Texts in StatisticsEditor: New York, NY : Springer New York, 2011Edición: 4Descripción: XXII, 494 p. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9781441998163Tema(s): Statistics | Mathematical statistics | Statistics | Statistical Theory and MethodsFormatos físicos adicionales: Printed edition:: Sin títuloClasificación CDD: 519.5 Clasificación LoC:QA276-280Recursos en línea: Libro electrónicoTexto
Contenidos:
Introduction -- Estimation -- Testing -- One-Way ANOVA -- Multiple Comparison Techniques -- Regression Analysis -- Multifactor Analysis of Variance -- Experimental Design Models -- Analysis of Covariance -- General Gauss-Markov Models -- Split Plot Models -- Mixed Models and Variance Components -- Model Diagnostics -- Variable Selection -- Collinearity and Alternative Estimates.-.
En: Springer eBooksResumen: This textbook provides a wide-ranging introduction to the use and theory of linear models for analyzing data. The author's 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: ANOVA, estimation including Bayesian estimation, hypothesis testing, multiple comparisons, regression analysis, and experimental design models. In addition, the book covers topics that are not usually treated at this level, but which are important in their own right: balanced incomplete block designs, testing for lack of fit, testing for independence, models with singular covariance matrices, variance component estimation, best linear and best linear unbiased prediction, collinearity, and variable selection. This new edition includes a more extensive discussion of best prediction and associated ideas of R2, as well as new sections on inner products and perpendicular projections for more general spaces and Milliken and Graybill’s generalization of Tukey’s one degree of freedom for nonadditivity test.
Star ratings
    Valoración media: 0.0 (0 votos)
Existencias
Tipo de ítem Biblioteca actual Colección Signatura Copia número Estado Fecha de vencimiento Código de barras
Libro Electrónico Biblioteca Electrónica
Colección de Libros Electrónicos QA276 -280 (Browse shelf(Abre debajo)) 1 No para préstamo 372310-2001

Introduction -- Estimation -- Testing -- One-Way ANOVA -- Multiple Comparison Techniques -- Regression Analysis -- Multifactor Analysis of Variance -- Experimental Design Models -- Analysis of Covariance -- General Gauss-Markov Models -- Split Plot Models -- Mixed Models and Variance Components -- Model Diagnostics -- Variable Selection -- Collinearity and Alternative Estimates.-.

This textbook provides a wide-ranging introduction to the use and theory of linear models for analyzing data. The author's 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: ANOVA, estimation including Bayesian estimation, hypothesis testing, multiple comparisons, regression analysis, and experimental design models. In addition, the book covers topics that are not usually treated at this level, but which are important in their own right: balanced incomplete block designs, testing for lack of fit, testing for independence, models with singular covariance matrices, variance component estimation, best linear and best linear unbiased prediction, collinearity, and variable selection. This new edition includes a more extensive discussion of best prediction and associated ideas of R2, as well as new sections on inner products and perpendicular projections for more general spaces and Milliken and Graybill’s generalization of Tukey’s one degree of freedom for nonadditivity test.

19

Con tecnología Koha