Probability and statistics

From the author of the bestselling "e;Analysis of Time Series,"e; Time-Series Forecasting offers a comprehensive, up-to-date review of forecasting methods.

The book presents a statistical theory for a class of nonlinear time-series models.

Randomization, Masking, and Allocation Concealment is indispensable for any trial researcher who wants to use state of the art randomization methods, and also wants to be able to describe these methods correctly.

Monte Carlo simulation has become an essential tool in the pricing of derivative securities and in risk management.

Routine applications of advanced statistical methods on real data have become possible in the last ten years because desktop computers have become much more powerful and cheaper.

Die zunehmende Bedeutung der Statistik hat zur Folge, dass grundlegende Kennt­ nisse der statistischen Methodenlehre notwendig sind, um gesellschaftliche wie betriebliche Zusammenhänge erkennen und darstellen zu können.

Questo libro offre un approccio moderno alla teoria dei processi stocastici in tempo continuo e del calcolo differenziale stocastico.

This book presents new findings on nonregular statistical estimation.

Explores regular structures in graphs and contingency tables by spectral theory and statistical methods This book bridges the gap between graph theory and statistics by giving answers to the demanding questions which arise when statisticians are confronted with large weighted graphs or rectangular arrays.

The only introduction you''ll need to start programming in R.

Modern marketing managers need intuitive and effective tools not just for designing strategies but also for general management.

This book covers advancements across business domains in knowledge and information management.

Quantum Probability and Related Topics is a series of volumes whose goal is to provide a picture of the state of the art in this rapidly growing field where classical probability, quantum physics and functional analysis merge together in an original synthesis which, for 20 years, has been enriching these three areas with new ideas, techniques and results.

Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities.

This book is aimed at researchers, graduate students and engineers who would like to be initiated to Piecewise Deterministic Markov Processes (PDMPs).

This book frames and demonstrates the best of modern morphometric methods, bridging the gap between biostatistics and organismal biology.

Das Buch bietet eine integrierte Darstellung der deskriptiven Statistik, moderner Methoden der explorativen Datenanalyse und der induktiven Statistik, einschließlich der Regressions- und Varianzanalyse.

This book focuses on statistical inferences related to various combinatorial stochastic processes.

Applied Probability and Stochastic Processes, Second Edition presents a self-contained introduction to elementary probability theory and stochastic processes with a special emphasis on their applications in science, engineering, finance, computer science, and operations research.

This book covers the aspects of R most often used by statistical analysts.

This book discusses various problems in stochastic Processes, Control Theory, Electromagnetics, Classical and Quantum Field Theory & Quantum Stochastics.

A clear easy-to-read guide to presenting your message using statistical data Poor presentation of data is everywhere; basic principles are forgotten or ignored.

This book presents the latest developments in the theory of gradient flows in random walk spaces.

This book presents the latest developments in the theory and applications of time series analysis and forecasting.

In a world of increasing financial uncertainty and growing unemployment, the macroeconomic contribution of SMEs is more important than ever.

This book concentrates on linear regression, path analysis and logistic regressions, the most used statistical techniques for the test of causal relationships.

Structural equation modeling (SEM) is a very general and flexible multivariate technique that allows relationships among variables to be examined.

This textbook provides a step-by-step introduction to the class of vine copulas, their statistical inference and applications.

This comprehensive book is an introduction to multilevel Bayesian models in R using brms and the Stan programming language.

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

"Statistiken sind merkwürdige Dinge .

This book aims to work out the distributed economic operation in smart grids in a systematic way, which ranges from model-based to model-free perspectives.

This two-volume set constitutes the refereed post-conference proceedings of the 25th International Conference on Enterprise Information Systems, ICEIS 2023, which was held in Prague, Czech Republic, during April 2023.

In the past 15 to 20 years, the computer has become a popular tool for exploring the relationship between a measured response and factors thought to affect the response.

Nonstandard Analysis enhances mathematical reasoning by introducing new ways of expression and deduction.

Statistics for Business explains the fundamentals of statistical analysis in a lucid, pragmatic way.

This book provides practical demonstrations of how to carry out definite integrals with Monte Carlo methods using Mathematica.

Applied probability is a broad research area that is of interest to scientists in diverse disciplines in science and technology, including: anthropology, biology, communication theory, economics, epidemiology, finance, geography, linguistics, medicine, meteorology, operations research, psychology, quality control, sociology, and statistics.

Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions.

Practical Statistical Methods: A SAS Programming Approach presents a broad spectrum of statistical methods useful for researchers without an extensive statistical background.

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A complete guide to cutting-edge techniques and best practices for applying covariance analysis methods The Second Edition of Analysis of Covariance and Alternatives sheds new light on its topic, offering in-depth discussions of underlying assumptions, comprehensive interpretations of results, and comparisons of distinct approaches.

Most approaches to crime analysis focus on geographical crime mapping, which is helpful in identifying crime clusters and allocating police resources, but does not explain why a particular crime took place.

An Update of the Most Popular Graduate-Level Introductions to Bayesian Statistics for Social ScientistsNow that Bayesian modeling has become standard, MCMC is well understood and trusted, and computing power continues to increase, Bayesian Methods: A Social and Behavioral Sciences Approach, Third Edition focuses more on implementation details of th

This book provides an introduction to measurement theory for non-specialists.

Praise for the Second Edition "e;This book has never had a competitor.