Introduction to the Theory of Statistical Inference
Hannelore Liero
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Bayesian Networks : With Examples in R
Marco Scutari
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Bayesian Modeling and Computation in Python
Osvaldo A. Martin
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Bayes Rules! : An Introduction to Applied Bayesian Modeling
Alicia A. Johnson
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Applied Linear Regression for Longitudinal Data : With an Emphasis on Missing Observations
Frans E.S. Tan
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Bayesian Thinking in Biostatistics
Gary L (Johns Hopkins University, Baltimore, Maryland, USA) Rosner
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Randomization, Bootstrap and Monte Carlo Methods in Biology
Bryan F.J. (University of Otago, Dunedin, New Zealand) Manly
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Time Series for Data Science : Analysis and Forecasting
Wayne A. (Southern Methodist University, Dallas, Texas, USA) Woodward
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Probability and Statistical Inference : From Basic Principles to Advanced Models
Miltiadis C. (Imperial College London, United Kingdom) Mavrakakis
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Probability and Statistical Inference : From Basic Principles to Advanced Models
Miltiadis C. Mavrakakis
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Surrogates : Gaussian Process Modeling, Design, and Optimization for the Applied Sciences
Robert B. (Virginia Tech Department of Statistics, USA) Gramacy
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Introduction to Probability, Second Edition
Joseph K. Blitzstein
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Statistical Analysis of Reliability Data
Martin J. Crowder
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Design and Analysis of Experiments and Observational Studies using R
Nathan (University of Toronto, Canada) Taback
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Stochastic Processes with R : An Introduction
Olga (California State University, Long Beach, USA) Korosteleva
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Practical Multivariate Analysis
Abdelmonem (University of California, Los Angeles, USA) Afifi
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Stochastic Processes : From Applications to Theory
Pierre Del Moral
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Discrete Data Analysis with R : Visualization and Modeling Techniques for Categorical and Count Data
Michael Friendly
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Graphics for Statistics and Data Analysis with R
Kevin J. (University of Northern British Columbia, Prince George Keen
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