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Multivariate Statistical Modelling Based on Generalized Linear Models

The book is aimed at applied statisticians, graduate students of statistics, and students and resear;...

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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;

Vergelijkbare producten zoals Data Analysis Using Hierarchical Generalized Linear Models with R

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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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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A First Course in Linear Model Theory

selection, and missing data. A new chapter on generalized linear models (Chapter 12). A new section on multivariate linear models in Chapter 13;

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Introduction to General and Generalized Linear Models

Bridging the gap between theory and practice for modern statistical model building, Introduction to General and Generalized Linear Models;

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Statistical Modelling in Biostatistics and Bioinformatics

are presented throughout each of the four areas, with some intriguing new ideas on hierarchical generalized non-linear models and on frailty;

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Statistical Modelling in Biostatistics and Bioinformatics

are presented throughout each of the four areas, with some intriguing new ideas on hierarchical generalized non-linear models and on frailty;

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Confidence Intervals in Generalized Regression Models

generalized regression model (GRM)-of various types of regression models. It also uses a likelihood-based approach for performing statistical;

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Confidence Intervals in Generalized Regression Models

generalized regression model (GRM)-of various types of regression models. It also uses a likelihood-based approach for performing statistical;

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Introduction to Applied Bayesian Statistics and Estimation for Social Scientists

regression model, generalized linear models, hierarchical models, and multivariate regression models - and it thoroughly develops each real-data;

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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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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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Statistical Modelling by Exponential Families

This book is a readable, digestible introduction to exponential families, encompassing statistical models based on the most useful;

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Statistical Modelling by Exponential Families

This book is a readable, digestible introduction to exponential families, encompassing statistical models based on the most useful;

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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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Robust Nonparametric Statistical Methods

methods based on transform-retransform techniques in multivariate models Taking a comprehensive, unified approach to statistical analysis, the;

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In All Likelihood

Based on a course in the theory of statistics this text concentrates on what can be achieved using the likelihood/Fisherian method;

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Multivariate Statistics

The book aims to present a wide range of the newest results on multivariate statistical models, distribution theory and applications;

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Statistical Models of Characteristics of Metal Vapor Lasers

In this book, various multivariate statistical techniques are applied in order to assess and predict the experiment. There are developed;

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An Introduction to Generalized Linear Models

on Bayesian analysis. Like its predecessor, this edition presents the theoretical background of generalized linear models (GLMs) before;

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Linear Model Theory

analysis and for developing new statistical methods. Most books on the subject have historically discussed univariate, multivariate, and mixed;

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Statistical Models in S

, generalized linear models, additive models, local regression, and tree-based models. The contributions of the ten authors-most of whom work in the;

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Statistical Inference For Models With Multivariate T-Distrib

the development of linear statistical models with applications to engineering, the physical sciences, and mathematics * Contains an up-to-date;

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Generalized, Linear, and Mixed Models

An accessible and self-contained introduction to statistical models-now in a modernized new edition Generalized, Linear, and Mixed Models;

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Generalized Linear Mixed Models

focuses on data-driven processes and provides context for extending traditional linear model thinking to generalized linear mixed modeling. See;

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