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Paola Lecca
Identifiability and Regression Analysis of Biological Systems Models

This richly illustrated book presents the latest techniques for the identifiability analysis and standard and robust regression analysis of complex dynamical models, and looks at their objectives. It begi…

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Edward C. Waymire, Rabi Bhattacharya
Continuous Parameter Markov Processes and Stochastic Differential Equations

This graduate text presents the elegant and profound theory of continuous parameter Markov processes and many of its applications. The authors focus on developing context and intuition before formalizing …

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Dose Finding and Beyond in Biopharmaceutical Development

This book covers topics in 2 parts: 1) Review of FDA Guidance, 2) Novel Designs and Analyses. While covering basic principles of dose finding, this book details advancements made in drug development.Findi…

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Rinaldo B. Schinazi
Classical and Spatial Stochastic Processes

This textbook provides an accessible approach to concepts and applications of stochastic processes ideal for a wide range of readers. This revised third edition features an intuitive reorganization with c…

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Lothar Sachs, Jürgen Hedderich
Applied Statistics

This standard work on statistical methods in life sciences and medicine provides easily understandable, illustrative, and practical guidance to students, lecturers and practitioners alike, covering all ne…

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String Processing and Information Retrieval

This book constitutes the refereed proceedings of the 31st International Symposium on String Processing and Information Retrieval, SPIRE 2024, held in Puerto Vallarta, Mexico, during September 23¿25, 2024…

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Nonparametric Bayesian Inference

This book is a compilation of unpublished papers written by Jean-Marie Rolin (with several co-authors) on nonparametric bayesian estimation. Jean-Marie was professor of statistics at University of Louvain…

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Theory and Applications of Time Series Analysis

This book presents the latest developments in the theory and applications of time series analysis and forecasting. Comprising a selection of refereed papers, it is divided into several parts that address …

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Marcel van Oijen
Bayesian Compendium

This book describes how Bayesian methods work. Aiming to demystify the approach, it explains how to parameterize and compare models while accounting for uncertainties in data, model parameters and model s…

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Norbert Henze
Asymptotic Stochastics

This textbook, which is based on the second edition of a book that has been previously published in German language, provides a comprehension-oriented introduction to asymptotic stochastics. It is aimed a…

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Gilles Pagès, Harald Luschgy
Marginal and Functional Quantization of Stochastic Processes

Vector Quantization, a pioneering discretization method based on nearest neighbor search, emerged in the 1950s primarily in signal processing, electrical engineering, and information theory. Later in the …

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Statistical Methods at the Forefront of Biomedical Advances

This book presents novel statistics methods and reproducible software that helps to solve challenging problems in biomedicine. Specifically, it consists of a collection of 11 chapters contributed by some …

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Tamás Rudas
Lectures on Advanced Topics in Categorical Data Analysis

This book continues the mission of the previous text by the author, Lectures on Categorical Data Analysis, by expanding on the introductory concepts from that volume and providing a mathematically rigorou…

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Emma Horton, Andreas E. Kyprianou
Stochastic Neutron Transport

This monograph highlights the connection between the theory of neutron transport and the theory of non-local branching processes. By detailing this frequently overlooked relationship, the authors provide …

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Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications

This volume presents a selection of articles on statistical modeling and simulation, with a focus on different aspects of statistical estimation and testing problems, the design of experiments, reliabilit…

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Guillaume Mercère
Data Driven Model Learning for Engineers

The main goal of this comprehensive textbook is to cover the core techniques required to understand some of the basic and most popular model learning algorithms available for engineers, then illustrate th…

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Hang Lee
Foundations of Applied Statistical Methods

This book covers methods of applied statistics for researchers who design and conduct experiments, perform statistical inference, and write technical reports. These research activities rely on an adequate…

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Henning Omre, Ole Bernhard Forberg, Torstein M. Fjeldstad
Bayesian Spatial Modelling with Conjugate Prior Models

This book offers a comprehensive overview of statistical methodology for modelling and evaluating spatial variables useful in a variety of applications. These spatial variables fall into three categories:…

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Recent Advances in Econometrics and Statistics

This volume presents a unique collection of original research contributions by leading experts in several modern fields of econometrics and statistics, including high-dimensional, nonparametric and robust…

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Time Series and Wavelet Analysis

Prof. Pedro A. Morettin is a Distinguished Professor of Statistics at the Institute of Mathematics and Statistics of the University of São Paulo (IME-USP), where he has built an academic career spanning a…

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