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Mathematical Modeling in Physical Sciences

This volume gathers selected papers presented at the ICMSQUARE 2023 - 12th International Conference on Mathematical Modeling in Physical Sciences held in Belgrade, Serbia from August 28-31, 2023. This pro…

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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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Quantitative Approaches to Microcirculation

Microcirculation is a key area of interest within the realms of biology and medicine. As a vital discipline, microcirculatory biology forms a significant part of established medical fields like cardiovasc…

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Rand R. Wilcox
A Guide to Robust Statistical Methods

Robust statistical methods are now being used in a wide range of disciplines. The appeal of these methods is that they are designed to perform about as well as classic techniques when standard assumptions…

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Ilija Barukcic
Theoriae causalitatis principia mathematica

Dive into a treasure trove of knowledge with over 1,332 equations, 34 detailed figures, and 81 comprehensive tables. Perfect for students, researchers, and enthusiasts seeking clarity and precision. This …

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Zden¿k Dostál, Tomá¿ Kozubek, Marie Sadowská, Vít Vondrák
Scalable Algorithms for Contact Problems

This book presents a comprehensive treatment of recently developed scalable algorithms for solving multibody contact problems of linear elasticity. The brand-new feature of these algorithms is their theor…

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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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Edward Gunning, Norma Bargary, Andrew J. Harrison, John Warmenhoven
Functional Data Analysis in Biomechanics

This book provides a concise discussion of fundamental functional data analysis (FDA) techniques for analysing biomechanical data, along with an up-to-date review of their applications. The core of the bo…

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William C. Bauldry
Computational Calculus

This book offers readers the methods that are necessary to apply the power of calculus to analyze real problems. While most calculus textbooks focus on formula-based calculus, this book explains how to do…

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William Seltzer, Margo Anderson
Use and Misuse of the United States Census

The U.S. government counts the American population every 10 years, and uses the resulting numbers in formulas to allocate seats in the House of Representative and Electoral College, and to make public fun…

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Olivier Wintenberger, Thomas Mikosch
Extreme Value Theory for Time Series

This book deals with extreme value theory for univariate and multivariate time series models characterized by power-law tails. These include the classical ARMA models with heavy-tailed noise and financial…

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Anestis Antoniadis, Jairo Cugliari, Jean-Michel Poggi, Yannig Goude
Statistical Learning Tools for Electricity Load Forecasting

This monograph explores a set of statistical and machine learning tools that can be effectively utilized for applied data analysis in the context of electricity load forecasting. Drawing on their substant…

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Developments in Statistical Modelling

This volume on the latest developments in statistical modelling is a collection of refereed papers presented at the 38th International Workshop on Statistical Modelling, IWSM 2024, held from 14 to 19 July…

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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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Daniel Sorensen
Statistical Learning in Genetics

This book provides an introduction to computer-based methods for the analysis of genomic data. Breakthroughs in molecular and computational biology have contributed to the emergence of vast data sets, whe…

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Micha¿ Chorowski, Ryszard Kutner, Tomasz Gubiec
Anomalous Stochastics

This textbook provides a comprehensive exploration of anomalous stochastic processes and extreme events, commonly referred to as "black swans," with a particular focus on (multi-)fractal approac…

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Graham Upton
A Modern Introduction to Probability and Statistics

Probability and statistics are subjects fundamental to data analysis, which, in turn, is essential for efficient artificial intelligence.

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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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Biostatistics Modeling and Public Health Applications

This book provides an overview and compilation of contemporary topics and innovative approaches in biostatistical modeling through their applications to evidence-based public health research and decision-…

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