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Nicolas Privault
Discrete Stochastic Processes

This text presents selected applications of discrete-time stochastic processes that involve random interactions and algorithms, and revolve around the Markov property. It covers recurrence properties of (…

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Steven T. Hackman, Antonius B. Dieker
QPLEX: A Computational Modeling and Analysis Methodology for Stochastic Systems

This book introduces QPLEX, a powerful computational framework designed for modeling and analyzing nonstationary stochastic systems with large state spaces. The methodology excels at rapidly and accuratel…

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Jim Albert, Maria Rizzo
R by Example

Now in its second edition, R by Example is an example-based introduction to the statistical computing environment that does not assume any previous familiarity with R or other software packages. R functio…

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Statistical Modeling Using Bayesian Latent Gaussian Models

This book focuses on the statistical modeling of geophysical and environmental data using Bayesian latent Gaussian models. The structure of these models is described in a thorough introductory chapter, wh…

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Frank Acito
Predictive Analytics with KNIME

This book is about data analytics, including problem definition, data preparation, and data analysis. A variety of techniques (e.g., regression, logistic regression, cluster analysis, neural nets, decisio…

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Giacomo Ascione, Yuliya Mishura, Enrica Pirozzi
Fractional Deterministic and Stochastic Calculus

Fractional calculus has emerged as a powerful and effective mathematical tool in the study of several phenomena in science and engineering. This text addressed to researchers, graduate students, and pract…

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Joseph Boffa
AI Assisted Business Analytics

This book explains the primary path to success, using software designed to sample and analyze cashflow and then link that analysis, with forecasting and market research. The case study will start with a s…

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Statistical Machine Learning for Engineering with Applications

This book offers a leisurely introduction to the concepts and methods of machine learning. Readers will learn about classification trees, Bayesian learning, neural networks and deep learning, the design o…

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Partial Least Squares Path Modeling

Now in its second edition, this edited book presents recent progress and techniques in partial least squares path modeling (PLS-PM), and provides a comprehensive overview of the current state-of-the-art i…

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Recent Advances in the Message Passing Interface

This volume LNCS constitutes the refereed proceedings of 31st European MPI Users' Group Meeting, EuroMPI 2024, held in Perth, WA, Australia, during September 25-27, 2024.The 8 full papers presented here w…

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Jingjing Ye, Lei Nie
Innovative Designs and Analyses for Small Population Clinical Trials

This book discusses a multidisciplinary and multi-stakeholder collaborative approach to small population clinical trials. It provides and illustrates a systematic framework that depends upon a collaborati…

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Biostatistics in Biopharmaceutical Research and Development

The Deming Conference on Applied Statistics has long been deemed an influential event in the biostatistics and biopharmaceutical profession. It provides learning experience on recent developments in stati…

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Biostatistics in Biopharmaceutical Research and Development

The Deming Conference on Applied Statistics has long been deemed an influential event in the biostatistics and biopharmaceutical profession. It provides learning experience on recent developments in stati…

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Matthias Templ
Visualization and Imputation of Missing Values

This book explores visualization and imputation techniques for missing values and presents practical applications using the statistical software R. It explains the concepts of common imputation methods wi…

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Bayesian Statistics, New Generations New Approaches

This book hosts the results presented at the 6th Bayesian Young Statisticians Meeting 2022 in Montréal, Canada, held on June 22-23, titled "Bayesian Statistics, New Generations New Approaches". …

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George J. Knafl
Modeling Correlated Outcomes Using Extensions of Generalized Estimating Equations and Linear Mixed Modeling

Introduction. - Part I Continuous, Count, and Dichotomous Outcomes. - 2. Standard GEE Modeling of Correlated Univariate Outcomes. - 3. Partially Modified GEE Modeling of Correlated Univariate Outcomes. - …

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Computing Technologies and Applied Mathematics

This proceedings volume convenes revised, selected works presented at the 3rd International Seminar on Computing Technologies and Applied Mathematics (CTAM2024), held at Komsomolsk-na-Amure State Universi…

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Krishna Garikipati
Data-driven Modelling and Scientific Machine Learning in Continuum Physics

This monograph takes the reader through recent advances in data-driven methods and machine learning for problems in science-specifically in continuum physics. It develops the foundations and details a num…

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Andrea Bellavia
Statistical Methods for Environmental Mixtures

This book provides a comprehensive introduction to statistical approaches for the assessment of complex environmental exposures, such as pollutants and chemical mixtures, within the exposome framework. En…

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Stochastic Geometry: Percolation, Tesselations, Gaussian Fields and Point Processes

An Introduction to Russo-Seymour-Welsh Theory.- 2. Random Tessellations - An Overview of Models.- 3. Gaussian Fields through Geometrical Properties.- 4. Complex Gaussian Zeros and Eigenvalues.- 5. Point P…

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