Statistics

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Spatial Point Patterns: Methodology and Applications with R

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Adrian Baddeley, Ege Rubak, Rolf Turner
November 24, 2015

Modern Statistical Methodology and Software for Analyzing Spatial Point Patterns Spatial Point Patterns: Methodology and Applications with R shows scientific researchers and applied statisticians from a wide range of fields how to analyze their spatial point pattern data. Making the techniques acces...

Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data

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Michael Friendly, David Meyer
December 17, 2015

An Applied Treatment of Modern Graphical Methods for Analyzing Categorical Data Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data presents an applied treatment of modern methods for the analysis of categorical data, both discrete response data and fr...

Fundamentals of Probability: with Stochastic Processes, Third Edition

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Saeed Ghahramani
November 6, 2015

Fundamentals of Probability with Stochastic Processes, Third Edition teaches probability in a natural way through interesting and instructive examples and exercises that motivate the theory, definitions, theorems, and methodology. The author takes a mathematically rigorous approach while closely adh...

Joint Modeling of Longitudinal and Time-to-Event Data

Robert Elashoff, Gang li, Ning Li
August 24, 2016

Longitudinal studies often incur several problems that challenge standard statistical methods for data analysis. These problems include non-ignorable missing data in longitudinal measurements of one or more response variables, informative observation times of longitudinal data, and survival...

Future Sustainable Ecosystems: Complexity, Risk, and Uncertainty

Nathaniel Kenneth Newlands
August 23, 2016

Future Sustainable Ecosystems: Complexity, Risk, Uncertainty provides an interdisciplinary, integrative overview of environmental problem-solving using statistics. It shows how statistics can be used to solve diverse environmental and socio-economic problems involving food, water, energy scarcity,...

Applied Biclustering Methods for Big and High-Dimensional Data Using R

Adetayo Kasim, Ziv Shkedy, Sebastian Kaiser, Sepp Hochreiter, Willem Talloen
August 23, 2016

Proven Methods for Big Data Analysis As big data has become standard in many application areas, challenges have arisen related to methodology and software development, including how to discover meaningful patterns in the vast amounts of data. Addressing these problems, Applied Biclustering...

Process Control Techniques for High-Volume Production

M. Kemal Atesmen
August 23, 2016

This book details most common statistical process control tools with many examples for high-volume production. It aims to make elements of high-volume production process control simple and easy to understand. It lets you thoroughly understand process controls instead of blindly trusting software...

Complex Survey Data Analysis with SAS

Taylor H. Lewis
August 23, 2016

Complex Survey Data Analysis with SAS® is an invaluable resource for applied researchers analyzing data generated from a sample design involving any combination of stratification, clustering, unequal weights, or finite population correction factors. After clearly explaining how the presence of...

Mixture Model-Based Classification

Paul D. McNicholas
August 19, 2016

This work addresses classification using mixture models broadly. Unlike traditional treatments of the subject that heavily focus on unsupervised approaches, this book gives attention to unsupervised, semi-supervised, and supervised classification paradigms. Case studies illustrate both non-Gaussian...

Hidden Markov Models for Time Series: An Introduction Using R, Second Edition

Walter Zucchini, Iain L. MacDonald, Roland Langrock
August 17, 2016

Hidden Markov Models for Time Series: An Introduction Using R, Second Edition illustrates the great flexibility of hidden Markov models (HMMs) as general-purpose models for time series data. The book provides a broad understanding of the models and their uses. After presenting the basic model...

Handbook of Item Response Theory, Volume One: Models

Wim J. van der Linden
August 15, 2016

Drawing on the work of internationally acclaimed experts in the field, Handbook of Item Response Theory, Volume One: Models presents all major item response models. This first volume in a three-volume set covers many model developments that have occurred in item response theory (IRT) during the...

A First Course in Machine Learning, Second Edition

Simon Rogers, Mark Girolami
August 15, 2016

"A First Course in Machine Learning by Simon Rogers and Mark Girolami is the best introductory book for ML currently available. It combines rigor and precision with accessibility, starts from a detailed explanation of the basic foundations of Bayesian analysis in the simplest of settings, and goes...

Statistical Techniques for Neuroscientists

Young K. Truong, Mechelle M. Lewis
August 12, 2016

Statistical Techniques for Neuroscientists introduces new and useful methods for data analysis involving simultaneous recording of neuron or large cluster (brain region) neuron activity. The statistical estimation and tests of hypotheses are based on the likelihood principle derived from stationary...

Data Analysis for the Life Sciences with R

Rafael A. Irizarry, Michael I. Love
August 10, 2016

This book covers several of the statistical concepts and data analytic skills needed to succeed in data-driven life science research. The authors proceed from relatively basic concepts related to computed p-values to advanced topics related to analyzing highthroughput data. They include the R code...

Big Data and Social Science: A Practical Guide to Methods and Tools

Ian Foster, Rayid Ghani, Ron S. Jarmin, Frauke Kreuter, Julia Lane
August 09, 2016

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Conferences

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