Graphical Models in Applied Multivariate Statistics by J Whittaker
- It reveals the interrelationships between multiple variables and features of the underlying conditional independence. - It covers conditional independence, several types of independence graphs, Gaussian models, issues in model selection, regression and decomposition. - Many numerical examples and exercises with solutions are included.-
Introductory Statistics for Business and Economics
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Applied Longitudinal Analysis
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Biostatistics
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Sample Size Determination and Power
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Statistical Methods for Survival Data Analysis
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Applied Econometric Times Series
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Bayesian Analysis for the Social Sciences
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An Elementary Introduction to Statistical Learning Theory
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The Statistical Analysis of Failure Time Data
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Regression Models for Time Series Analysis
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Loss Models
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Statistical Rules of Thumb
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Bayesian Theory
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Introduction to Linear Regression Analysis
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Aspects of Multivariate Statistical Theory
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Fundamentals of Queueing Theory
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Statistics of Extremes
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Structural Equations with Latent Variables
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Nonparametric Statistical Methods
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Applied Linear Regression
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Models for Investors in Real World Markets
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Regression Analysis by Example
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Directional Statistics
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Statistical Intervals
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An Introduction to Probability Theory and Its Applications, Volume 2
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System Reliability Theory
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An Introduction to Categorical Data Analysis
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Markov Decision Processes
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Applied Logistic Regression
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Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators
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Probability and Measure
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| ISBN 13 | |
| ISBN 10 | |
| Title | Graphical Models in Applied Multivariate Statistics |
| Author | J Whittaker |
| Series | |
| Condition | Unavailable |
| Binding Type | |
| Publisher | |
| Year published | |
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| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |
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