Probability 1

Harness the power of randomness (and Python code) to solve real-world problems in fun, hands-on experimentsーfrom simulating evolution to encrypting messages to making machine-learning algorithms! T……続きを見る

With the rapid development of big data, three major challenges arise in the field of economics and management. The first challenge is that the traditional correlation-based methods cannot essentiall……続きを見る

Features recent trends and advances in the theory and techniques used to accurately measure and model growth Growth Curve Modeling: Theory and Applications features an accessible introduction to gro……続きを見る

Winner of the 2024 De Groot Prize awarded by the International Society for Bayesian Analysis (ISBA) Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds your knowledge of and……続きを見る

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 acc……続きを見る

This open access book provides a comprehensive treatment of recent developments in kernel-based identification that are of interest to anyone engaged in learning dynamic systems from data. The reade……続きを見る

This open access book provides an introduction to uncertainty quantification in engineering. Starting with preliminaries on Bayesian statistics and Monte Carlo methods, followed by material on imprec……続きを見る

This book covers seismic probabilistic risk assessment (S-PRA) and related studies which have become more important to increase the safety of nuclear facilities against earthquakes and tsunamis in t……続きを見る

This open access book collects expert contributions on actuarial modelling and related topics, from machine learning to legal aspects, and reflects on possible insurance designs during an epidemic/p……続きを見る

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 framewo……続きを見る

This open access book focuses on both the theory and practice associated with the tools and approaches for decisionmaking in the face of deep uncertainty. It explores approaches and tools supporting……続きを見る

This book demonstrates how nonlinear/non-Gaussian Bayesian time series estimation methods were used to produce a probability distribution of potential MH370 flight paths. It provides details of how ……続きを見る

This open access book addresses the physical phenomenon of events that seem to occur spontaneously and without any known cause. These are to be contrasted with events that happen in a (pre-)determin……続きを見る

This open access book focuses on robot introspection, which has a direct impact on physical human–robot interaction and long-term autonomy, and which can benefit from autonomous anomaly monitoring a……続きを見る

**Recommended by Bill Gates A thought-provoking and wide-ranging exploration of machine learning and the race to build computer intelligences as flexible as our own** In the world's top research lab……続きを見る

Time Series: A First Course with Bootstrap Starter provides an introductory course on time series analysis that satisfies the triptych of (i) mathematical completeness, (ii) computational illustrati……続きを見る

This open access book focuses on the interplay between random walks on planar maps and Koebe’s circle packing theorem. Further topics covered include electric networks, the He–Schramm theorem on inf……続きを見る

An intermediate-level treatment of Bayesian hierarchical models and their applications, this book demonstrates the advantages of a Bayesian approach to data sets involving inferences for collections……続きを見る

Practice your way to a higher statistics score The adage that "practice makes perfect" is never truer than with math problems. Statistics Workbook For Dummies with Online Practice provides succinct ……続きを見る

This textbook offers a compact introductory course on Malliavin calculus, an active and powerful area of research. It covers recent applications, including density formulas, regularity of probabilit……続きを見る

An Introduction to Generalized Linear Models, Fourth Edition provides a cohesive framework for statistical modelling, with an emphasis on numerical and graphical methods. This new edition of a bests……続きを見る

Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or mean imputation, only work under highly restrictive conditions, which are often not met in practice. Mu……続きを見る

**Beginner's Guide to Correlation Analysis: Learn The One Reason Your Correlation Results Are Probably Wrong** Ever wondered why your correlation results seem off? There's one crucial factor you mig……続きを見る

Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As cont……続きを見る

'The book provides a comprehensive review of the DRM approach to data fusion. It is well written and easy to follow, although the technical details are not trivial. The authors did an excellent job ……続きを見る

Considering Poisson random measures as the driving sources for stochastic (partial) differential equations allows us to incorporate jumps and to model sudden, unexpected phenomena. By using such equ……続きを見る

Provides an in-depth treatment of ANOVA and ANCOVA techniques from a linear model perspective ANOVA and ANCOVA: A GLM Approach provides a contemporary look at the general linear model (GLM) approach……続きを見る

The book is composed of two main parts: mathematical background and queueing systems with applications. The mathematical background is a self containing introduction to the stochastic processes of t……続きを見る

From classical foundations to advanced modern theory, this self-contained and comprehensive guide to probability weaves together mathematical proofs, historical context and richly detailed illustrat……続きを見る

Generalized Linear Mixed Models: Modern Concepts, Methods, and Applications (2nd edition) presents an updated introduction to linear modeling using the generalized linear mixed model (GLMM) as the o……続きを見る