Probability and statistics

This book addresses and disseminates research and development in the applications of intelligent techniques for computer vision, the field that works on enabling computers to see, identify, and process images in the same way that human vision does, and then providing appropriate output.

The components of variance is a notion essential to statisticians and quantitative research scientists working in a variety of fields, including the biological, genetic, health, industrial, and psychological sciences.

This book closes the gap between what people think Excel can do and what they can achieve in the tool.

Categorical Statistics for CommunicationResearch presents scholars with a discipline-specific guide to categorical data analysis.

Human beings are competitive.

This book introduces the major concepts of probability and statistics, along with the necessary computational tools, for undergraduates and graduate students.

Introductory Statistics for the Behavioral Sciences is a workbook on statistical procedures and formulas that are relevant to research and field work.

Methods of Statistical Model Estimation examines the most important and popular methods used to estimate parameters for statistical models and provide informative model summary statistics.

The author describes the current state of the art in the theory of invariant random fields.

The process of developing predictive models includes many stages.

This book introduces readers to the fundamentals of creating presentation graphics using R, based on 111 detailed and complete scripts.

Statistical Methods for Dynamic Treatment Regimes shares state of the art of statistical methods developed to address questions of estimation and inference for dynamic treatment regimes, a branch of personalized medicine.

This is the age of data.

Sparse models are particularly useful in scientific applications, such as biomarker discovery in genetic or neuroimaging data, where the interpretability of a predictive model is essential.

This book is a how-to guide on statistical analyses designed for undergraduates and others new to the subject.

In 1992, when Paul Erdos was awarded a Doctor Honoris Causa by Charles University in Prague, a small conference was held, bringing together a distin- guished group of researchers with interests spanning a variety of fields related to Erdos' own work.

This book provides a thorough understanding of distribution theory and data analysis using statistical software to solve problems related to basic statistics, probability models, and simulation.

Contains Nearly 100 Pages of New MaterialThe recent financial crisis has shown that credit risk in particular and finance in general remain important fields for the application of mathematical concepts to real-life situations.

This textbook highlights the many practical uses of stable distributions, exploring the theory, numerical algorithms, and statistical methods used to work with stable laws.

A fascinating chronicle of the lives and achievements of the menand women who helped shapethe science of statistics This handsomely illustrated volume will make enthralling readingfor scientists, mathematicians, and science history buffs alike.

"Nichtparametrische Datenanalyse" enthält eine umfassende Darstellung von nichtparametrischen Methoden zur statistischen Modellierung und Auswertung von Experimenten, wobei viele seit langem bekannte Verfahren in einer neuartigen Sichtweise beschrieben werden.

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This book constitutes the proceedings of the 23rd International Conference on Information Processing in Medical Imaging, IPMI 2013, held in Asilomar in June/July 2013.

Clear, rigorous, and intuitive, Markov Processes provides a bridge from an undergraduate probability course to a course in stochastic processes and also as a reference for those that want to see detailed proofs of the theorems of Markov processes.

The book introduces to the reader a number of cutting edge statistical methods which can e used for the analysis of genomic, proteomic and metabolomic data sets.

About fifteen years ago Henning Rodhe and I disscussed the calculation of residence times, or lifetimes, of certain air pollutants for the first time.

Bayesian nonparametrics has grown tremendously in the last three decades, especially in the last few years.

Conceiving reliablesystems is a strategic issue for any industrial society.

This book presents the effective combination of mathematical statistics, general metrology, and textile metrology to allow data analysis with regard to the evaluation of parameters of fibrous structures.

In this book, the optimal transportation problem (OT) is described as a variational problem for absolutely continuous stochastic processes with fixed initial and terminal distributions.

This textbook introduces the use of Python programming for exploring and modelling data in the field of Earth Sciences.

This Brief introduces engineers to the main principles in ethics, research design, statistics, and publishing of human subject research.

Introducing a groundbreaking framework for stochastic partial differential equations (SPDEs), this work presents three significant advancements over the traditional variational approach.

This richly illustrated book presents the objectives of, and the latest techniques for, the identifiability analysis and standard and robust regression analysis of complex dynamical models.

Contributions in this volume focus on computationally efficient algorithms and rigorous mathematical theories for analyzing large-scale networks.

This book develops the theory of continuous and discrete stochastic processes within the context of cell biology.

The Advances in Applied Mechanics book series draws together recent significant advances in various topics in applied mechanics.

This book constitutes the proceedings of the 29th International Conference on Case-Based Reasoning, ICCBR 2021, which took place in Salamanca, Spain, during September 13-16, 2021.

This monograph investigates violations of statistical stability of physical events, variables, and processes and develops a new physical-mathematical theory taking into consideration such violations - the theory of hyper-random phenomena.

A rigorous and self-contained exposition of aggregation functions and their properties.

This book fulfills the global need to evaluate measurement results along with the associated uncertainty.

This is a short book on the fundamental concepts of the no-arbitrage theory of pricing financial derivatives.

This text is a step-by-step guide for students taking a first course in statistics for social work and for social work managers and practitioners who want to learn how to use Excel to solve practical statistics problems in in the workplace, whether or not they have taken a course in statistics.

Memetic algorithms are evolutionary algorithms that apply a local search process to refine solutions to hard problems.

Despite research interest in functional data analysis in the last three decades, few books are available on the subject.

Geometry and Martingales in Banach Spaces provides a compact exposition of the results explaining the interrelations existing between the metric geometry of Banach spaces and the theory of martingales, and general random vectors with values in those Banach spaces.

Particle simulation of semiconductor devices is a rather new field which has started to catch the interest of the world's scientific community.

Essentials of Probability Theory for Statisticians provides graduate students with a rigorous treatment of probability theory, with an emphasis on results central to theoretical statistics.