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Linear Model Theory

A precise and accessible presentation of linear model theory, illustrated with data examples Statisticians often use linear models for data;

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Univariate and Multivariate General Linear Models

Reviewing the theory of the general linear model (GLM) using a general framework, Univariate and Multivariate General Linear Models: Theory;

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Univariate and Multivariate General Linear Models

Reviewing the theory of the general linear model (GLM) using a general framework, Univariate and Multivariate General Linear Models: Theory;

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Reduced Forms of Rational Expectations Models

multivariate and non-linear models.;

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Univariate and Multivariate General Linear Models

both general linear model theory and application. The model is discussed using a general framework, enabling students to appreciate fully the;

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Time Series Models

. The emphasis is on understanding how time series are analyzed and models constructed. Familiarity with calculus, linear algebra, and;

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Robust Nonparametric Statistical Methods

univariate tests and estimates with extensions to linear models, multivariate models, times series models, experimental designs, and mixed models. It;

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Linear Time Series with MATLAB and OCTAVE

This book presents an introduction to linear univariate and multivariate time series analysis, providing brief theoretical insights into;

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Linear Time Series with MATLAB and Octave

This book presents an introduction to linear univariate and multivariate time series analysis, providing brief theoretical insights into;

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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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Regression And Time Series Model Selection

selection techniques for univariate and multivariate regression models, univariate and multivariate autoregressive models, nonparametric (including;

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Multivariate Analysis with LISREL

), generalized linear models, multilevel analysis, and principal component analysis. It provides numerous examples from several disciplines and discusses;

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Multivariate, Multilinear and Mixed Linear Models

This book presents the latest findings on statistical inference in multivariate, multilinear and mixed linear models, providing a holistic;

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Statistical Tolerance Regions

multivariate linear regression model General mixed models Bayesian tolerance intervals A final chapter contains coverage of miscellaneous topics;

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An Introduction to Stochastic Orders

areas such as reliability, survival analysis, risks, finance, and economics. The book provides a general background on this topic for students;

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Applied Multivariate Statistics with R

for a wide array of multivariate statistical applications. Chapters cover graphical displays; linear algebra; univariate, bivariate and;

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A Course in Time Series Analysis

presentations on vector ARMA models, cointegration, and multivariate linear systems. Special features include: * Contributions from eleven of the;

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Personalized Predictive Modeling in Type 1 Diabetes

) regression technique (linear or non-linear), (iii) learning mechanism (batch or sequential), (iv) development and testing procedure and (v) scaling;

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Asymptotics, Nonparametrics, and Time Series

Contains over 2500 equations and exhaustively covers not only nonparametrics but also parametric, semiparametric, frequentist, Bayesian;

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A Primer on Linear Models

of the general linear model, including multiple regression models, one-way ANOVA, mixed-effects models, and time series models. It then;

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A Primer on Linear Models

of the general linear model, including multiple regression models, one-way ANOVA, mixed-effects models, and time series models. It then;

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Asymptotics, Nonparametrics, and Time Series

"Contains over 2500 equations and exhaustively covers not only nonparametrics but also parametric, semiparametric, frequentist, Bayesian;

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Time Series and Panel Data Econometrics

This book is concerned with recent developments in time series and panel data techniques for the analysis of macroeconomic and financial;

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Multivariate Bonferroni-Type Inequalities

inequalities and demands new insights into linear and Frechet optimality. The book explores these advances in bounding techniques with corresponding;

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Multivariate Bonferroni-Type Inequalities

inequalities and demands new insights into linear and Frechet optimality. The book explores these advances in bounding techniques with corresponding;

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Nonlinear Statistical Models

A comprehensive text and reference bringing together advances in the theory of probability and statistics and relating them to applications;

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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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