Pattern Recognition and Machine Learning (Information Science and Statistics)
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Statistical Inference
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Data Analysis Using Regression and Multilevel/Hierarchical Models
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The Elements of Statistical Learning
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Probability and Statistics, 3rd Edition
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Pattern Classification (2nd Edition)
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Bayesian Data Analysis, Second Edition (Texts in Statistical Science)
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Categorical Data Analysis (Wiley Series in Probability and Statistics)
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Testing Statistical Hypotheses (Springer Texts in Statistics)
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Monte Carlo Statistical Methods (Springer Texts in Statistics)
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Probability Theory: The Logic of Science
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Introductory Statistics with R
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Bayesian Statistics: An Introduction (Arnold Publication)
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Information Theory, Inference & Learning Algorithms
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Modern Applied Statistics with S
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All of Nonparametric Statistics (Springer Texts in Statistics)
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Introduction to Time Series and Forecasting
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Data Analysis and Graphics Using R
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Convex Optimization
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Mathematical Statistics
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Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning)
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Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
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Understanding Complex Datasets: Data Mining with Matrix Decompositions (Chapman & Hall/Crc Data Mining and Knowledge Discovery Series)
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Learning Bayesian Networks (Artificial Intelligence)
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Semi-Supervised Learning (Adaptive Computation and Machine Learning)
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Numerical Analysis for Statisticians
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Principles of Statistical Inference
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Kernel Methods for Pattern Analysis
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In All Likelihood: Statistical Modelling and Inference Using Likelihood
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The Bayesian Choice: From Decision-Theoretic Foundations to Computational Implementation (Springer Texts in Statistics)
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