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Robust Mixed Model Analysis

models.This research monograph provides a comprehensive account of methods of mixed model analysis that are robust in various aspects, such as to;

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Robust Methods in Biostatistics

classes of models: Linear regression Generalized linear models Linear mixed models Marginal longitudinal data models Cox survival analysis model;

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Applied Mixed Model Analysis

of mixed model analysis, including two-level and three-level structures, and covers continuous outcome variables, dichotomous outcome variables;

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Applied Mixed Model Analysis

of mixed model analysis, including two-level and three-level structures, and covers continuous outcome variables, dichotomous outcome variables;

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Multi model Jumping Systems Robust Filtering and Fault Detection

combining stochastic jumping system, neural network and fuzzy models. It focuses on robust filtering, including finite-time robust filtering, finite;

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Mixed Effects Models for Complex Data

semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values;

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Mixed Effects Models for Complex Data

semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values;

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Linear and Generalized Linear Mixed Models and Their Applications

who are interested in using mixed models for statistical data analysis.;

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Linear and Generalized Linear Mixed Models and Their Applications

who are interested in using mixed models for statistical data analysis.;

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Linear Mixed Models for Longitudinal Data

This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this;

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Extending The Linear Model With R

count models, linear discriminant analysis, and sandwich and robust estimation for generalized linear models (GLMs) Revised chapters on random;

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Robust Systems Theory and Applications

used in linear robust control analysis/synthesis and in robust (control-oriented) identification. The main analysis and design methods are;

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Robust Nonparametric Statistical Methods

Presenting an extensive set of tools and methods for data analysis, Robust Nonparametric Statistical Methods, Second Edition covers;

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Modeling in Mathematics

representing noisy sounds with short-time sinusoids, robust Bayesian regularized estimation based on regression model and robust quadratic regression;

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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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Frontiers In Statistics

diagnostics, robust multivariate analysis, single index models and wavelets.This volume is dedicated to Prof. Peter J Bickel in honor of his 65th;

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Frontiers In Statistics

diagnostics, robust multivariate analysis, single index models and wavelets.This volume is dedicated to Prof. Peter J Bickel in honor of his 65th;

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Univariate and Multivariate General Linear Models

-of-profiles model, the SUR model, the CGMANOVA model, HLM, mixed models, and the analysis of repeated measures with missing data.;

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Handbook of Mixed Membership Models and Their Applications

factor analysis, and describe nonparametric mixed membership models. They also present extensions of the mixed membership model for text analysis;

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Handbook of Mixed Membership Models and Their Applications

factor analysis, and describe nonparametric mixed membership models. They also present extensions of the mixed membership model for text analysis;

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Variable Mixed-mode Fatigue Delamination in Composite Laminates - Testing and Analysis

of variable mixed-mode fatigue delamination in composite laminates. A mixed-mode fatigue delamination model is proposed. Opposite to literature mixed;

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Non-monotonic Approach to Robust H? Control of Multi-model Systems

Non-monotonic Approach to Robust H8 Control of Multi-model Systems focuses on robust analysis and synthesis problems for multi-model;

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Analysis and Synthesis of Fuzzy Control Systems

lack of tools for systematic stability analysis and controller design. To address this problem, many model-based fuzzy control approaches have;

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Analysis and Synthesis of Fuzzy Control Systems

lack of tools for systematic stability analysis and controller design. To address this problem, many model-based fuzzy control approaches have;

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Mixed-Effects Models in S and S-PLUS

An overview of the theory and application of linear and nonlinear mixed-effects models in the analysis of grouped data, such as;

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Mixed-Effects Models in S and S-PLUS

An overview of the theory and application of linear and nonlinear mixed-effects models in the analysis of grouped data, such as;

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System Design and Control Integration for Advanced Manufacturing

. Little work considers model information for robust design particularly for the dynamic system. This book covers robust design for both static and;

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