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Dynamic Linear Models with R

. After a detailed introduction to general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis;

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A First Course in Linear Model Theory

studying the theory and applications of both univariate and multivariate linear models. In addition to adding R functionality, this second edition;

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Linear Models with R

. Linear Models with R, Second Edition explains how to use linear models in physical science, engineering, social science, and business;

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An R Companion to Linear Statistical Models

Focusing on user-developed programming, An R Companion to Linear Statistical Models serves two audiences: those who are familiar with the;

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An R Companion to Linear Statistical Models

Focusing on user-developed programming, An R Companion to Linear Statistical Models serves two audiences: those who are familiar with the;

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Recursive Models of Dynamic Linear Economies

apply competitive equilibria for a class of linear-quadratic-Gaussian dynamic economies with complete markets. Their book, based on the 2012;

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Time Series Analysis

With a focus on analyzing and modeling linear dynamic systems using statistical methods, Time Series Analysis formulates various linear;

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Extending The Linear Model With R

expanded both in popularity and in the number of packages available. Extending the Linear Model with R: Generalized Linear, Mixed Effects and;

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An Introduction to Generalized Additive Models with R

Generalized Additive Models: An Introduction with R imparts a thorough understanding of the theory and practical applications of GAMs and;

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Recursive Models of Dynamic Linear Economies

of linear-quadratic-Gaussian dynamic economies with complete markets. Their book, based on the 2012 Gorman lectures, stresses heterogeneity;

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Advanced R Statistical Programming and Data Models

, researchers, or students who are familiar with R and basic statistical techniques such as linear regression and who want to learn how to use R to;

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Extending the Linear Model with R

. Faraway's critically acclaimed Linear Models with R examined regression and analysis of variance, demonstrated the different methods;

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Dynamic Linear Economic Models

their applications in the construction and analysis of dynamic economic models. It explains the theory of linear difference equations and;

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Dynamic Linear Economic Models

their applications in the construction and analysis of dynamic economic models. It explains the theory of linear difference equations and;

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Functional Data Analysis with R and MATLAB

as spline basis functions, data smoothing, curve registration, functional linear models and dynamic systems Functional data analysis is put;

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Foundations of Linear and Generalized Linear Models

of linear mixed models and generalized linear mixed models with random effects for clustered correlated data, Bayesian modeling, and extensions to;

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R for Finite Element Analyses of Size dependent Microscale Structures

requisite linear elastic theory and highlight the implemented R functions. Each chapter concludes with a brief summary and relevant references.;

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Linear Models

dynamic relationships that these models have with Analysis of Variance (ANOVA), experimental design, and random and mixed-model effects. This one;

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Bayesian Analysis of Linear Models

models and models not generally studied by statisticianssuch as linear dynamic systems and changing parameter models ... and somethingpractical;

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Bayesian Analysis of Linear Models

models and models not generally studied by statisticianssuch as linear dynamic systems and changing parameter models ... and somethingpractical;

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Multivariate Generalized Linear Mixed Models Using R

Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound models for analyzing large and complex data;

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Generalized Linear Mixed Models

picture. It shows how linear models fit with the rest of the core statistics curriculum and points out the major issues that statistical modelers;

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Data Analysis Using Hierarchical Generalized Linear Models with R

advanced statistical modelling including generalized linear models with random effects, survival analysis and frailty models, multivariate HGLMs;

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Data Analysis Using Hierarchical Generalized Linear Models with R

advanced statistical modelling including generalized linear models with random effects, survival analysis and frailty models, multivariate HGLMs;

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Generalized Linear Models and Correlated Data Methods

-statistics majors or advanced undergraduate statistics majors Includes case studies with real data Offers material on R at the end of each chapter;

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Introduction to General and Generalized Linear Models

text, although other software packages are also discussed. Numerous examples show how the problems are solved with R. After describing the;

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Linear Models And Regression With R

Starting with the basic linear model where the design and covariance matrices are of full rank, this book demonstrates how the same;

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