Smart Data: State-of-the-Art Perspectives in Computing and Applications explores smart data computing techniques to provide intelligent decision making and prediction services support for business, science, and engineering.
This volume contains the reviews and poster papers presented at the workshop Solar Convection and Oscillations and their Relationship: SCORe '96, held in Arhus, Denmark, May 27 - 31, 1996.
Fixed point theory in probabilistic metric spaces can be considered as a part of Probabilistic Analysis, which is a very dynamic area of mathematical research.
This book constitutes the refereed proceedings of the 10th International Symposium on Algorithmic Game Theory, SAGT 2017, held in L'Aquila, Italy, in September 2017.
Advanced Computational Techniques for Sustainable Computing is considered multi-disciplinary field encompassing advanced computational techniques across several domain, including, Computer Science, Statistical Computation and Electronics Engineering.
Foundations of Risk Analysis presents the issues core to risk analysis understanding what risk means, expressing risk, building risk models, addressing uncertainty, and applying probability models to real problems.
Practical Business Statistics, Sixth Edition, is a conceptual , realistic, and matter-of-fact approach to managerial statistics that carefully maintains, but does not overemphasize, mathematical correctness.
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.
Exploring the World through Data We live in a data-driven world, and the goal of this text is to teach students how to access and analyse these data critically.
Linear Differential Equations and Oscillators is the first book within Ordinary Differential Equations with Applications to Trajectories and Vibrations, Six-volume Set.
This book provides a comprehensive introduction to statistical approaches for the assessment of complex environmental exposures, such as pollutants and chemical mixtures, within the exposome framework.
Intended as a self-contained introduction to measure theory, this textbook also includes a comprehensive treatment of integration on locally compact Hausdorff spaces, the analytic and Borel subsets of Polish spaces, and Haar measures on locally compact groups.
This book provides a brief but accessible introduction to a set of related, mathematical ideas that have proved useful in understanding the brain and behaviour.
This book gives an introduction to R to build up graphing, simulating and computing skills to enable one to see theoretical and statistical models in economics in a unified way.
Showcasing a discussion of the experimental process and a review of basic statistics, this volume provides methodologies to identify general data distribution, skewness, and outliers.
Master advanced topics in the analysis of large, dynamically dependent datasets with this insightful resource Statistical Learning with Big Dependent Data delivers a comprehensive presentation of the statistical and machine learning methods useful for analyzing and forecasting large and dynamically dependent data sets.
This book represents a compilation of experience from a slate of experts involved in developing and deploying Bayesian Networks (BN) for corrosion management.
HIGHLIGHTS THE USE OF BAYESIAN STATISTICS TO GAIN INSIGHTS FROM EMPIRICAL DATA Featuring an accessible approach, Bayesian Methods for Management and Business: Pragmatic Solutions for Real Problems demonstrates how Bayesian statistics can help to provide insights into important issues facing business and management.
This book describes and outlines the theoretical foundations of system simulation in teaching, and as a practical contribution to teaching-and-learning models.
Civil and environmental engineers need an understanding of mathematical statistics and probability theory to deal with the variability that affects engineers structures, soil pressures, river flows and the like.
Stochastic Process Limits are useful and interesting because they generate simple approximations for complicated stochastic processes and also help explain the statistical regularity associated with a macroscopic view of uncertainty.
Text Analytics: An Introduction to the Science and Applications of Unstructured Information Analysis is a concise and accessible introduction to the science and applications of text analytics (or text mining), which enables automatic knowledge discovery from unstructured information sources, for both industrial and academic purposes.
This book is a reference for librarians, mathematicians, and statisticians involved in college and research level mathematics and statistics in the 21st century.
This collection of contributions originates from the well-established conference series "e;Fractal Geometry and Stochastics"e; which brings together researchers from different fields using concepts and methods from fractal geometry.
The Most Comprehensive Book on the SubjectChronicles the Development of the Weibull Distribution in Statistical Theory and Applied StatisticsExploring one of the most important distributions in statistics, The Weibull Distribution: A Handbook focuses on its origin, statistical properties, and related distributions.
"e;Chemometrics with R"e; offers readers an accessible introduction to the world of multivariate statistics in the life sciences, providing a complete description of the general data analysis paradigm, from exploratory analysis to modeling to validation.
Continuous time parameter Markov chains have been useful for modeling various random phenomena occurring in queueing theory, genetics, demography, epidemiology, and competing populations.
Bioconductor is a widely used open source and open development software project for the analysis and comprehension of data arising from high-throughput experimentation in genomics and molecular biology.
This book reports on cutting-edge theories and methods for analyzing complex systems, such as transportation and communication networks and discusses multi-disciplinary approaches to dependability problems encountered when dealing with complex systems in practice.
This book presents techniques for determining uncertainties in numerical solutions with applications in the fields of business administration, civil engineering, and economics, using Excel as a computational tool.
Repeated Measures Design with Generalized Linear Mixed Models for Randomized Controlled Trials is the first book focused on the application of generalized linear mixed models and its related models in the statistical design and analysis of repeated measures from randomized controlled trials.
Great interest is now being shown in computational and mathematical neuroscience, fuelled in part by the rise in computing power, the ability to record large amounts of neurophysiological data, and advances in stochastic analysis.
