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Advanced Linear Models

This work details the statistical inference of linear models including parameter estimation, hypothesis testing, confidence intervals, and;

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Linear Models in Statistics

The essential introduction to the theory and application of linear models-now in a valuable new edition Since most advanced statistical;

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Advanced Linear Modeling

This book introduces several topics related to linear model theory, including: multivariate linear models, discriminant analysis, principal;

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Statistical Tests for Mixed Linear Models

An advanced discussion of linear models with mixed or random effects. In recent years a breakthrough has occurred in our ability to draw;

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Advanced R Statistical Programming and Data Models

data visualization, linear and advanced regression, additive models, survival / time to event analysis Handle machine learning using R;

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A First Course in Linear Model Theory

' study of advanced linear models, generalized linear models, nonlinear models, and dynamic models.;

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Generalized Linear Models and Correlated Data Methods

Offers a unified discussion of generalized linear models and correlated data methods Provides information suitable for graduate non;

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Linear and Integer Optimization

into two main parts. The first covers the theory of linear and integer optimization, including both basic and advanced topics. Dantzig's;

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Statistics for Linguists

uses of linear models through generalized models to more advanced approaches, maintaining its focus on conceptual issues and avoiding excessive;

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Statistics for Linguists

uses of linear models through generalized models to more advanced approaches, maintaining its focus on conceptual issues and avoiding excessive;

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Non-Linear Time Series Models in Empirical Finance

Although many of the models commonly used in empirical finance are linear, the nature of financial data suggests that non-linear models are;

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Non-Linear Time Series Models in Empirical Finance

Although many of the models commonly used in empirical finance are linear, the nature of financial data suggests that non-linear models are;

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Matrix Algebra for Linear Models

Linear Models is an ideal textbook for advanced undergraduate and graduate-level courses on statistics, matrices, and linear algebra. The book;

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An Introduction to Generalized Additive Models with R

related advanced models, enabling informed use of these very flexible tools. The author bases his approach on a framework of penalized regression;

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A First Course in Linear Models and Design of Experiments

This textbook presents the basic concepts of linear models, design and analysis of experiments. With the rigorous treatment of topics and;

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Linear and Non-linear Stability Analysis in Boiling Water Reactors

of multiple advanced linear and non linear signal processing methods, and includes analytical case studies of existing plants. This combination makes;

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Linear Algebra and Linear Models

Linear Algebra and Linear Models comprises a concise and rigorous introduction to linear algebra required for statistics followed by the;

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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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Linear Model Methodology

Given the importance of linear models in statistical theory and experimental research, a good understanding of their fundamental principles;

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Generalized Linear Models With Examples in R

applicable for both beginning and advanced students of applied statistics. Generalized linear models (GLMs) are powerful tools in applied;

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An Introduction to Generalized Linear Models

An Introduction to Generalized Linear Models, Fourth Edition provides a cohesive framework for statistical modelling, with an emphasis on;

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An Introduction to Generalized Linear Models

An Introduction to Generalized Linear Models, Fourth Edition provides a cohesive framework for statistical modelling, with an emphasis on;

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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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Introduction to Linear Models and Statistical Inference

' hands-on classroom experience and is tailored to reflect how students best learn to analyze linear relationships. The text begins with the;

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Advanced Statistics for the Behavioral Sciences

statistical analyses using the R software environment. The text opens with a foundational section on linear algebra, then covers a variety of advanced;

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SAS System for Linear Models, 4e + Linear Models in Statistics, 2e Set

This set contains: 9780471221746 SAS for Linear Models, Fourth Edition by Ramon Littell, Walter W. Stroup, Rudolf Freund and 9780471754985;

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