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Ronald W. Shonkwiler, Franklin Mendivil
Explorations in Monte Carlo Methods

Monte Carlo Methods are among the most used, and useful, computational tools available today. They provide efficient and practical algorithms to solve a wide range of scientific and engineering problems i…

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Nan Chen
Stochastic Methods for Modeling and Predicting Complex Dynamical Systems

This second edition is an essential guide to understanding, modeling, and predicting complex dynamical systems using new methods with stochastic tools. Expanding upon the original book, the author covers …

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Methodological and Applied Statistics and Demography III

This book of peer-reviewed short papers on methodological and applied statistics and demography is the third of four volumes from the 52nd Scientific Meeting of the Italian Statistical Society (SIS 2024),…

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Sinho Chewi, Jonathan Niles-Weed, Philippe Rigollet
Statistical Optimal Transport

This monograph aims to offer a concise introduction to optimal transport, quickly transitioning to its applications in statistics and machine learning. It is primarily tailored for students and researcher…

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Algorithms and Computational Theory for Engineering Applications

This book goes deeply into the world of algorithms and computational theory and its astounding influence on numerous engineering areas. The book's carefully chosen content highlights the most recent studi…

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Thomas W. Macfarland
Introduction to Data Science in Biostatistics

Introduction to Data Science in Biostatistics: Using R, the Tidyverse Ecosystem, and APIs defines and explores the term "data science" and discusses the many professional skills and competencies…

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Raymond J. Spiteri, Kyle Klenk
Extreme-Scale Computing

Part 1 - Extreme Scientific Computing Software Management.- Chapter 1 Linux Command Line.- Chapter 2: Version Control and Repositories.- Chapter 3: Building Software.- Part 2 - Programming Patterns and Mo…

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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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Daniel Sorensen
Statistical Learning in Genetics

Overview.- Part I: Fitting Likelihood and Bayesian Models.- 2. Likelihood.- 3. Computing the Likelihood.- 4. Bayesian Methods.- 5. McMC in Practice.- Part II: Prediction.- 6. Fundamentals of Prediction.- …

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

The U.S. government conducts a population census every 10 years, adds up the counts by geographic location, and uses the resulting numbers in formulas to allocate seats in the House of Representative and …

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Umberto Michelucci
Statistics for Scientists

This book offers researchers and practitioners a concise and accessible guide to the essential concepts in statistics, emphasizing their proper application. It encourages readers to delve deeper into the …

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Statistics for Innovation III

This book presents peer-reviewed short papers on methodological and applied statistical research presented at the Italian Statistical Society's international conference on "Statistics for Innovation&…

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Tsung-Wu Ho
Time Series Forecasting using Machine Learning

Preface.- Chapter 1 Time Series Basics in R.- Chapter 2 Predictive Time Series Modelling.- Chapter 3 Forecasting using Machine Learning Methods.- Chapter 4 Special Topics.- Chapter 5 Predictive Case Studi…

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Stochastic Geophysical Fluid Dynamics

This book is based on an Oberwolfach Seminar, and it intends to give an introduction and an overview to several directions of the recent research on stochastic geophysical fluid dynamics and to discuss di…

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Jolanta Misiewicz
A One-Semester Course on Probability

This concise textbook covers the full scope of an introductory course in modern probability theory, from elementary combinatorial methods to the central limit theorem, while maintaining mathematical rigor…

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Advances in Machine Learning and Big Data Analytics I

This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2023, that was held on May 29-30, 2023 by NERIST and NIT Arunachal Pradesh India) is intended to be used as a referenc…

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Potter C. Chang
Data Analysis of Medical Studies

This book is written for the many health professionals who are regularly frustrated by elegant but ambiguous descriptions of results of data analysis. It uses articles of the New England Journal of Medici…

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Alan J. King, Stein W. Wallace
Modeling with Stochastic Programming

This is an updated version of what is still the only text to address basic questions about how to model uncertainty in mathematical programming, including how to reformulate a deterministic model so that …

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