Probability and statistics

Collecting Bayesian material scattered throughout the literature, Current Trends in Bayesian Methodology with Applications examines the latest methodological and applied aspects of Bayesian statistics.

A Guide to Doing Statistics in Second Language Research Using SPSS and R, Second Edition is the only text available that demonstrates how to use SPSS and R as specifically related to applied linguistics and SLA research.

Das Buch richtet sich an alle Bachelor-Studierenden und Lehramts-Bachelor-Studierenden mit Fach Mathematik, die den Stoff der wichtigsten Grundvorlesungen durch Fragen und gegebene Antworten überprüfen, auffrischen und ergänzen wollen.

Since their introduction in 1972, generalized linear models (GLMs) have proven useful in the generalization of classical normal models.

The present book is devoted to studying optimal experimental designs for a wide class of linear and nonlinear regression models.

Dieses Buch stellt statistischen Verfahren und Kennzahlen vor, um Unsicherheiten in der industriellen Produktion zu analysieren und einzuschätzen.

This easy-to-follow applied book on semiparametric regression methods using R is intended to close the gap between the available methodology and its use in practice.

This book is the first exclusively devoted to the systematic synthesis of diagnostic test accuracy studies.

The Encyclopedia of Mathematical Geosciences is a complete and authoritative reference work.

This 2nd edition textbook offers a rigorous introduction to measure theoretic probability with particular attention to topics of interest to mathematical statisticians-a textbook for courses in probability for students in mathematical statistics.

This monograph treats the question of determining how much to spend for the collection and analysis of public data.

This book collects interrelated lectures on fractal dynamics, anomalous transport and various historical and modern aspects of plasma sciences and technology.

In an era dominated by mathematical and statistical models, this book unravels the profound significance of these tools in decoding uncertainties within numerical, observational, and calculation-based data.

With strong numerical and computational focus, this book serves as an essential resource on the methods for functional neuroimaging analysis, diffusion weighted image analysis, and longitudinal VBM analysis.

INLA stands for Integrated Nested Laplace Approximations, which is a new method for fitting a broad class of Bayesian regression models.

In a time when increasingly larger and complex data collections are being produced, it is clear that new and adaptive forms of data representation and analysis have to be conceived and implemented.

The book comprises original articles on topical issues of risk theory, rational decision making, statistical decisions, and control of stochastic systems.

This book constitutes the proceedings of the Research School on Statistics and Data Science, RSSDS 2019, held in Melbourne, VIC, Australia, in July 2019.

The final volume of this series presents a synopsis of the curriculum that a typical Six Sigma program should follow.

A modern approach to statistical learning and its applications through visualization methods With a unique and innovative presentation, Multivariate Nonparametric Regression and Visualization provides readers with the core statistical concepts to obtain complete and accurate predictions when given a set of data.

This book explores multiple types of innovation within the modern wine industry and how it has developed historically.

Interactions between species are of fundamental importance to all living systems and the framework we have for studying these interactions is community ecology.

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 2024 in Durham, UK.

Retaining all the material from the second edition and adding substantial new material, this third edition presents models and statistical methods for analyzing spatially referenced point process data.

Modern Directional Statistics collects important advances in methodology and theory for directional statistics over the last two decades.

Statistically Speaking is a book of quotations.

An Integrated Approach to Modeling and Optimization in Engineering and Science examines the effects of experimental design, mathematical modeling, and optimization processes for solving many different problems.

Hidden semi-Markov models (HSMMs) are among the most important models in the area of artificial intelligence / machine learning.

This title was originally published in 1974.

The first Pannonian Symposium on Mathematical Statistics was held at Bad Tatzmannsdorf (Burgenland/Austria) from September 16th to 21st, 1979.

The book gives a systematical presentation of stochastic approximation methods for models of American-type options with general pay-off functions for discrete time Markov price processes.

Winner of the 2016 De Groot Prize from the International Society for Bayesian AnalysisNow in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems.

Statistics for Physical Sciences is an informal, relatively short, but systematic, guide to the more commonly used ideas and techniques in statistical analysis, as used in physical sciences, together with explanations of their origins.

This textbook presents an exposition of stochastic dynamics and irreversibility.

Get started with an accelerated introduction to the R ecosystem, programming language, and tools including R script and RStudio.

Statistics are used throughout businesses to present and analyse data and decide on best practice.

Handbook of Survival Analysis presents modern techniques and research problems in lifetime data analysis.

Modern statistical software provides the ability to compute statistics in a timely, orderly fashion.

Most industrial and natural materials exhibit a macroscopic behaviour which results from the existence of microscale inhomogeneities.

This book offers a modern and accessible introduction to Statistical Inference, the science of inferring key information from data.

Although multifractals are rooted in probability, much of the related literature comes from the physics and mathematics arena.

Today econometrics has been widely applied in the empirical study of economics.

The book provides a comprehensive overview of the latest econometric methods for studying the dynamics of macroeconomic and financial time series.

Since the term "e;random ?

Provides an introduction to the diverse subject area of experimental design, with many practical and applicable exercises to help the reader understand, present and analyse the data.

This volume is composed of invited papers on learning and control.

This book introduces machine learning in finance and illustrates how we can use computational tools in numerical finance in real-world context.