Probability and statistics

Kernel smoothing refers to a general methodology for recovery of underlying structure in data sets.

This textbook will help graduate students in non-statistics disciplines, advanced undergraduate researchers, and research faculty in the health sciences to learn, use and communicate results from many commonly used statistical methods.

The genesis of this volume was in a one-day meeting arranged under the auspices of the Nathematical Ecology Group, jointly of the British Region of the Biometric Society and the British Ecological Society, and held in the Natural History Museum in London on the 4th May 1982.

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BRIDGES THE GAP BETWEEN SAS AND R, ALLOWING USERS TRAINED IN ONE LANGUAGE TO EASILY LEARN THE OTHER SAS and R are widely-used, very different software environments.

Energy distance is a statistical distance between the distributions of random vectors, which characterizes equality of distributions.

Statistical methods have become an increasingly important and integral part of research in the health sciences.

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This work provides descriptions, explanations and examples of the Bayesian approach to statistics, demonstrating the utility of Bayesian methods for analyzing real-world problems in the health sciences.

During the academic years 1972-1973 and 1973-1974, an intensive sem- inar on the foundations of quantum mechanics met at Stanford on a regular basis.

This book explores various renewal processes in the context of probability theory, uncertainty theory and chance theory.

Research Methodology is meant to provide a broad guideline to facilitate and steer the whole of a research activity in any discipline.

Longitudinal data are ubiquitous across Medicine, Public Health, Public Policy, Psychology, Political Science, Biology, Sociology and Education, yet many longitudinal data sets remain improperly analyzed.

Dieses Lehrbuch bietet einen leichten Einstieg und verständlichen Gesamtüberblick über die quantitativen und qualitativen Methoden der Psychologie und angrenzender Sozialwissenschaften: alle wichtigen Verfahren, ihre Logik und Einsatzgebiete, Stärken und Schwachpunkte und auch neuere Entwicklungen.

This book contains a novel theory of random fields estimation of Wiener type, developed originally by the author and presented here.

The richly illustrated Interactive Web-Based Data Visualization with R, plotly, and shiny focuses on the process of programming interactive web graphics for multidimensional data analysis.

This book offers the theory of causal analysis and its applications.

This is the second edition of Linear Models for Multivariate, Time Series and Spatial Data.

This book deals with certain important problems in Classical and Quantum Information Theory Quantum Information Theory, A Selection of Matrix Inequalities Stochastic Filtering Theory Applied to Electromagnetic Fields and Strings Wigner-distributions in Quantum Mechanics Quantization of Classical Field Theories Statistical Signal Processing Quantum Field Theory, Quantum Statistics, Gravity, Stochastic Fields and Information Problems in Information Theory It will be very helpful for students of Undergraduate and Postgraduate Courses in Electronics, Communication and Signal Processing.

Constructive Suggestions for Efficiently Implementing Technology Transfer Theory of Science and Technology Transfer and Applications presents the mechanisms, features, effects, and modes of technology transfer.

Hidden Markov Models for Time Series: An Introduction Using R, Second Edition illustrates the great flexibility of hidden Markov models (HMMs) as general-purpose models for time series data.

This book describes a maximally simple market risk model that is still practical and main risk measures like the value-at-risk and the expected shortfall.

This book explains the importance of using the probability that the hypothesis is correct (PHC), an intuitive measure that anyone can understand, as an alternative to the p-value.

This Handbook takes an econometric approach to the foundations of economic performance analysis.

R for College Mathematics and Statistics encourages the use of R in mathematics and statistics courses.

Asymptotic Geometric Analysis is concerned with the geometric and linear properties of finite dimensional objects, normed spaces, and convex bodies, especially with the asymptotics of their various quantitative parameters as the dimension tends to infinity.

This book provides an introduction to operational research methods and their application in the agrifood and environmental sectors.

This volume shows modern probabilistic methods in action: Brownian Motion Process as applied to the electrical phenomena investigated by Green et al.

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Generally, books on mathematical statistics are restricted to the case of independent identically distributed random variables.

This book focuses on the practical issues and approaches to handling longitudinal and multilevel data.

This book provides a unifying structure for the activities that fall under the process typically called "e;standard setting"e; on tests of proficiency.

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.

This textbook explores two distinct stochastic processes that evolve at random: weakly stationary processes and discrete parameter Markov processes.

A Novel Method to Analyze Problems and Encourage Systemic ThinkingReal-Life Case Studies Illustrate the Application of the Systemic Yoyo Model in Diverse AreasWritten by the co-creator of the systemic yoyo model, Systemic Yoyos: Some Impacts of the Second Dimension shows how the yoyo model and its methodology can be employed to study many unsettled

This book contains revised and significantly extended versions of selected papers from three workshops on Uncertainty Reasoning for the Semantic Web (URSW), held at the International Semantic Web Conferences (ISWC) in 2011, 2012, and 2013.

This book investigates the critical gain design in stochastic iterative learning control (SILC), including four specific gain design strategies: decreasing gain design, adaptive gain design, event-triggering gain design, and optimal gain design.

This is one of the first parallel computing books to focus exclusively on parallel data structures, algorithms, software tools, and applications in data science.

The simplest mathematical model of the Brownian motion of physics is the simple, symmetric random walk.

This book is devoted to the econometric analysis of linear multivariate rational expectation models.

The ongoing boom of applications for artificial intelligence (AI) is based on algorithms that were inspired by neuroscience discoveries in the 1960s.

Drug development is an iterative process.

This book serves as an introductory text in mathematical programming and optimization for students having a mathematical background that includes one semester of linear algebra and a complete calculus sequence.

This book finds a broad domain of relevance in statistics and the social sciences.

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 work is aimed at an audience with a sound mathematical background wishing to learn about the rapidly expanding ?

Reissuing works originally published between 1929 and 1991, this collection of 17 volumes presents a variety of considerations on Econometrics, from introductions to specific research works on particular industries.

Chance rules our daily lives in many different ways.