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Machine Learning A Practical Approach on the Statistical Learning Theory

Fundamentals of Probability and Stochastic Processes with Applications to Communications

Probabilistic Cellular Automata Theory, Applications and Future Perspectives

Strength in Numbers: The Rising of Academic Statistics Departments in the U. S.

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Bayesian Networks in R with Applications in Systems Biology

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Bayesian Hierarchical Space-Time Models with Application to Significant Wave Height

Community Structure of Complex Networks

Statistical Analysis of Climate Series Analyzing, Plotting, Modeling, and Predicting with R

Ship and Offshore Structure Design in Climate Change Perspective

Long-Memory Processes Probabilistic Properties and Statistical Methods

Advances in Theoretical and Applied Statistics

Introduction to Probability and Statistics for Engineers

Basics of Bioinformatics Lecture Notes of the Graduate Summer School on Bioinformatics of China

Handling Missing Data in Ranked Set Sampling

An Introduction to Order Statistics

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Applied Spatial Data Analysis with R

EnvStats An R Package for Environmental Statistics

The R Software Fundamentals of Programming and Statistical Analysis

Topics from the 8th Annual UNCG Regional Mathematics and Statistics Conference

Optimal Stochastic Control Schemes within a Structural Reliability Framework

Robustness in Statistical Forecasting

Gröbner Bases Statistics and Software Systems

Quantile-Based Reliability Analysis

Between Certainty and Uncertainty Statistics and Probability in Five Units with Notes on Historical Origins and Illustrative Numerical Examples

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Handbook of Computational Finance

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Computational Cancer Biology An Interaction Network Approach

Classification and Multivariate Analysis for Complex Data Structures

A Tiny Handbook of R

Statistics for High-Dimensional Data Methods, Theory and Applications

Bayesian Theory and Methods with Applications

Statistical Image Processing and Multidimensional Modeling

R for SAS and SPSS Users

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Introducing Monte Carlo Methods with R

Applied Probability

Multivariate Nonparametric Methods with R An approach based on spatial signs and ranks

Anwendungsorientierte Mathematik: Von Daten zur Funktion. Eine Einführung in die mathematische Modellbildung für Lehramtsstudierende

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Introductory Time Series with R

Principles and Theory for Data Mining and Machine Learning

Data Modeling for Metrology and Testing in Measurement Science

Bayesian Computation with R

Maximum Penalized Likelihood Estimation Volume II: Regression

R for SAS and SPSS Users

Introduction to Nonparametric Estimation

Information Theory and Statistical Learning

A First Course in Bayesian Statistical Methods

Social Computing and Behavioral Modeling

Statistics for Innovation Statistical Design of “Continuous” Product Innovation

Information Criteria and Statistical Modeling

Bayesian Networks and Influence Diagrams A Guide to Construction and Analysis

Simulation and Inference for Stochastic Differential Equations With R Examples

Analysis of Integrated and Cointegrated Time Series with R

Social Computing, Behavioral Modeling, and Prediction

Modern Multivariate Statistical Techniques Regression, Classification, and Manifold Learning

Advances in Mathematical and Statistical Modeling

Precision Landmark Location for Machine Vision and Photogrammetry Finding and Achieving the Maximum Possible Accuracy

Encyclopedia of GIS

Linear Models and Generalizations Least Squares and Alternatives

Mathematics – Key Technology for the Future Joint Projects Between Universities and Industry 2004–2007

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COMPSTAT 2008 Proceedings in Computational Statistics

Progress in Geomathematics

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Bayesian Networks and Decision Graphs February 8, 2007

Data Quality and Record Linkage Techniques

Matrix Algebra Theory, Computations, and Applications in Statistics

Bayesian Computation with R

Introduction to Probability with Statistical Applications

Bayesian Core: A Practical Approach to Computational Bayesian Statistics

Reliability, Life Testing and the Prediction of Service Lives For Engineers and Scientists

Information and Complexity in Statistical Modeling

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