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Graphical Models in Applied Multivariate Statistics

Graphical models----a subset of log--linear models----reveal the interrelationships between multiple variables and features of the;

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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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Applied Multivariate Statistics with SAS Software

Real-world problems and data sets are the backbone of this groundbreaking book. Applied Multivariate Statistics with SASA (R) Software;

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Applied Multivariate Analysis

areas of behavioral and social sciences where multivariate statistics is heavily applied. This new edition features an appendix of answers to;

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Multivariate Statistics

core topic. The first part of this book is devoted to graphical techniques. The second deals with multivariate random variables and presents;

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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 researchers with a strong interest;

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Handbook of Graphical Models

a wide audience, including graduate students, applied researchers, and experts in graphical models.;

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Handbook of Graphical Models

at a wide audience, including graduate students, applied researchers, and experts in graphical models.;

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Multivariate Statistics

to graphical techniques. The second part deals with multivariate random variables and presents the derivation of estimators and tests for;

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An R Companion for Applied Statistics II

An R Companion for Applied Statistics II: Multivariable and Multivariate Techniques breaks the language of the R software down into;

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Applied Multivariate Data Analysis

analysis may be undertaken. Now in its 2nd edition, 'Applied Multivariate Data Analysis' has been fully expanded and updated, including major;

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Graphics for Statistics and Data Analysis with R

of Applied Statistics Graphics for Statistics and Data Analysis with R, Second Edition, presents the basic principles of graphical design and applies;

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Graphics for Statistics and Data Analysis with R

Praise for the First Edition The main strength of this book is that it provides a unified framework of graphical tools for data;

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Multivariate Statistics

The book aims to present a wide range of the newest results on multivariate statistical models, dist;...

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Applied Multivariate Stat Analysis PNIE

For courses in Multivariate Statistics, Marketing Research, Intermediate Business Statistics, Statis;...

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Applied Statistics and Multivariate Data Analysis for Business and Economics

applications of applied statistics, statistical testing, and multivariate data analysis. Drawing on practical examples from the business world, it;

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Applied Statistics and Multivariate Data Analysis for Business and Economics

applications of applied statistics, statistical testing, and multivariate data analysis. Drawing on practical examples from the business world, it;

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High-Dimensional Covariance Estimation

shrinkage, thresholding, and penalized likelihood with applications to Gaussian graphical models, prediction, and mean-variance portfolio management;

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Multivariate Statistical Methods in Quality Management

graphical tools * Coax important hidden information from data with graphical 3-D software and numerical multivariate data stratification * Perform;

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Introduction to Applied Bayesian Statistics and Estimation for Social Scientists

This book outlines Bayesian statistical analysis in great detail, from the development of a model th;...

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Bilinear Regression Analysis

from linear models are extended and applied to tensor spaces. Further, the book considers decompositions of tensor products into natural;

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Modern Statistical Methods for Spatial and Multivariate Data

postdoctoral students interested in interdisciplinary research. Researchers in applied statistics and sciences will find this book an important;

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Applied Statistics I - International Student Edition

Created from the first half of Rebecca M. Warner's popular Applied Statistics: From Bivariate Through Multivariate Techniques, this;

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Linear Model Theory

needs a basic knowledge of statistics, probability, and inference, as well as a solid background in matrix theory and applied univariate linear;

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Multivariate Analysis for the Behavioral Sciences, Second Edition

contentious issues of p-values and confidence intervals are also discussed in the introductory chapter. After describing graphical methods, the;

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Multivariate Analysis for the Behavioral Sciences, Second Edition

contentious issues of p-values and confidence intervals are also discussed in the introductory chapter. After describing graphical methods, the book;

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