Summarizing developments and techniques in the field, this reference covers sample surveys, nonparametric analysis, hypothesis testing, time series analysis, Bayesian inference, and distribution theory for applications in statistics, economics, medicine, biology, engineering, sociology, psychology, and information technology.
This lecture provides an introduction to the field of mobile robotics and the intersection between multiple robotics-related disciplines including electrical, mechanical, computer, software engineering and computer science.
Recent advances in brain science measurement technology have given researchers access to very large-scale time series data such as EEG/MEG data (20 to 100 dimensional) and fMRI (140,000 dimensional) data.
Dieses Lehrbuch wendet sich hauptsächlich an Studierende der Ingenieur- und Naturwissenschaften sowie der Informatik, aber auch an in der angewandten Praxis tätige Absolventen dieser Disziplinen.
Limit theorems for stochastic processes are an important part of probability theory and mathematical statistics and one model that has attracted the attention of many researchers working in the area is that of limit theorems for randomly stopped stochastic processes.
Unlike other books about R, written from the perspective of statistics, this book is written from the perspective of programmers, providing a channel for programmers with expertise in other programming languages to quickly understand R.
Psychological Statistics: The Basics walks the reader through the core logic of statistical inference and provides a solid grounding in the techniques necessary to understand modern statistical methods in the psychological and behavioral sciences.
"e;Transport Processes in Space Physics and Astrophysics"e; is aimed at graduate level students to provide the necessary mathematical and physics background to understand the transport of gases, charged particle gases, energetic charged particles, turbulence, and radiation in an astrophysical and space physics context.
This book presents a systematic overview of cutting-edge research in the field of parametric modeling of personal income and wealth distribution, which allows one to represent how income/wealth is distributed within a given population.
Financial engineering has been proven to be a useful tool for risk management, but using the theory in practice requires a thorough understanding of the risks and ethical standards involved.
Interest in statistical methodology is increasing so rapidly in the astronomical community that accessible introductory material in this area is long overdue.
This book offers an introductory-level guide to the complex field of multivariate analytical calibration, with particular emphasis on real applications such as near infrared spectroscopy.
Statistical Analysis of Management Data provides a comprehensive approach to multivariate statistical analyses that are important for researchers in all fields of management, including finance, production, accounting, marketing, strategy, technology, and human resources.
Statistics and Analysis of Scientific Data covers the foundations of probability theory and statistics, and a number of numerical and analytical methods that are essential for the present-day analyst of scientific data.
Chemical data analysis, with aspects of metrology in chemistry and chemometrics, is an evolving discipline where new and better ways of doing things are constantly being developed.
Analysis of Failure and Survival Data is an essential textbook for graduate-level students of survival analysis and reliability and a valuable reference for practitioners.
This book presents the fundamental theoretical notions of supervised machine learning along with a wide range of applications using Python, R, and Stata.
Long-term monitoring is of fundamental significance in solving many important problems in astrophysics and, furthermore, has unequalled value in extending observational runs with small telescopes for the education of young astronomers in order to teach them how to secure high-quality observational data over many years.
The measurement of dependability attributes on real systems is a very time-consuming and costly affair, making analytical or simulation modeling the only viable solutions.
Measuring the abundance of individuals and the diversity of species are core components of most ecological research projects and conservation monitoring.
Probabilistic Methods in Applied Mathematics, Volume 3 focuses on the influence of the probability theory on the formulation of mathematical models and development of theories in many applied fields.
ADVANCES IN HEAVY TAILED RISK MODELING A cutting-edge guide for the theories, applications, and statistical methodologies essential to heavy tailed risk modeling Focusing on the quantitative aspects of heavy tailed loss processes in operational risk and relevant insurance analytics, Advances in Heavy Tailed Risk Modeling: A Handbook of Operational Risk presents comprehensive coverage of the latest research on the theories and applications in risk measurement and modeling techniques.
Statistics is central in the biosciences, social sciences and other disciplines, yet many students often struggle to learn how to perform statistical tests, and to understand how and why statistical tests work.
This book tells the story of the probability integral, the approaches to analyzing it throughout history, and the many areas of science where it arises.
For students in industrial and systems engineering (ISE) and operations research (OR) to understand optimization at an advanced level, they must first grasp the analysis of algorithms, computational complexity, and other concepts and modern developments in numerical methods.
This volume, the fourth of the quantum probability series, collects part of the contributions to the Year of Quantum Probability organized by the Volterra Center of University of Rome II.
Directional data arise in the form of circular / semicircular / axial, symmetric / asymmetric, uni / bimodal data, in practical situations of varied fields.
Incorporating more than 20 years of the editors' and contributors' statistical work in mixed membership modeling, this handbook shows how to use these flexible modeling tools to uncover hidden patterns in modern high-dimensional multivariate data.
This book presents a unified approach to the problem of inequality, combining results from a variety of research fields - the human life cycle, group dynamics, networks, markets, and economic geography.
