Probability and statistics

This work is devoted to several problems of parametric (mainly) and nonparametric estimation through the observation of Poisson processes defined on general spaces.

The success of the first edition of Generalized Linear Models led to the updated Second Edition, which continues to provide a definitive unified, treatment of methods for the analysis of diverse types of data.

Nursing is a growing area of higher education, in which anintroduction to statistics is an essential component.

A complete user''s guide to structural equations explaining the underlying principals and practical implementation of these methods.

This book provides a captivating journey through the realms of classical and quantum systems as it unravels the profound influence that noise may have on their static and dynamic properties.

Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization describes such algorithms as Locally Linear Embedding (LLE), Laplacian Eigenmaps, Isomap, Semidefinite Embedding, and t-SNE to resolve the problem of dimensionality reduction in the case of non-linear relationships within the data.

This guide offers a clear step-by-step approach for graduate students and early-career researchers, especially non-native English speakers, seeking to publish in international journals in the social sciences.

This volume provides an introduction to the theory of Mean Field Games, suggested by J.

Bayesian analysis is one of the important tools for statistical modelling and inference.

The book provides an extensive introduction to queueing models driven by Levy-processes as well as a systematic account of the literature on Levy-driven queues.

Master the Statistical Techniques for Six Sigma Operations, While Boosting Your Excel and Minitab Skills!

The First Book Dedicated to This Class of Longitudinal ModelsAlthough antedependence models are particularly useful for modeling longitudinal data that exhibit serial correlation, few books adequately cover these models.

Recent Developments in Clustering and Data Analysis presents the results of clustering and multidimensional data analysis research conducted primarily in Japan and France.

A traditional approach to developing multivariate statistical theory is algebraic.

This second of two Exercises in Analysis volumes covers problems in five core topics of mathematical analysis: Function Spaces, Nonlinear and Multivalued Maps, Smooth and Nonsmooth Calculus, Degree Theory and Fixed Point Theory, and Variational and Topological Methods.

Biostatistics for Clinical and Public Health Research provides a concise overview of statistical analysis methods.

A textbook on the use of advanced statistical methods in healthcare sciencesPrimer of Applied Regression & Analysis of Variance is a textbook especially created for medical, public health, and social and environmental science students who need applied (not theoretical) training in the use of statistical methods.

Spreadsheet Problem Solving and Programming for Engineers and Scientists provides a comprehensive resource essential to a full understanding of modern spreadsheet skills needed for engineering and scientific computations.

This volume provides an overview of two of the most important examples of interacting particle systems, the contact process, and the voter model, as well as their many variants introduced in the past 50 years.

This textbook discusses central statistical concepts and their use in business and economics.

This book provides a new analytical approach for dynamic data repeatedly measured from multiple subjects over time.

A concise, practical guide in statistical methods for experimental data handling; ideal for course use and a handy reference for researchers.

How do you learn about what's going on in the world?

This book is about data analytics, including problem definition, data preparation, and data analysis.

The first six chapters of this volume present the author's 'predictive' or information theoretic' approach to statistical mechanics, in which the basic probability distributions over microstates are obtained as distributions of maximum entropy (Le.

Essential Statistical Methods for Medical Statistics presents only key contributions which have been selected from the volume in the Handbook of Statistics: Medical Statistics, Volume 27 (2009).

Newcomers to R are often intimidated by the command-line interface, the vast number of functions and packages, or the processes of importing data and performing a simple statistical analysis.

A textbook for a graduate course in the theory of distributions and related topics, for students of applied mathematics or theoretical physics.

Philosophy of Probability provides a comprehensive introduction to theoretical issues that occupy a central position in disciplines ranging from philosophy of mind and epistemology to cognitive science, decision theory and artificial intelligence.

A wide range of topics and perspectives in the field of statistics are brought together in this volume.

This book provides in-depth and wide-ranging analyses of the emergence, and subsequent ubiquity, of algorithms in diverse realms of social life.

This volume contains the proceedings of the XII Symposium of Probability and Stochastic Processes which took place at Universidad Autonoma de Yucatan in Merida, Mexico, on November 16-20, 2015.

Statistical Analysis of Questionnaires: A Unified Approach Based on R and Stata presents special statistical methods for analyzing data collected by questionnaires.

This book constitutes the refereed post-conference proceedings of the Fourth International Conference on IoT as a Service, IoTaaS 2018, which took place in Xi'an, China, in November 2018.

This book describes how to establish data science and analytics capabilities in organisations using Emergent Design, an evolutionary approach that increases the chances of successful outcomes while minimising upfront investment.

The second edition of this volume provides insight and practical illustrations on how modern statistical concepts and regression methods can be applied in medical prediction problems, including diagnostic and prognostic outcomes.

The main goal of this comprehensive textbook is to cover the core techniques required to understand some of the basic and most popular model learning algorithms available for engineers, then illustrate their applicability directly with stationary time series.

Probability is an area of mathematics of tremendous contemporary importance across all aspects of human endeavour.

Neue Möglichkeiten der Datenerhebung mittels digitaler Technologien, aber auch die Verfügbarkeit prozessproduzierter Daten, die bei der Nutzung sozialer Medien, Smartphones oder sogenannter Wearables anfallen, bergen ein enormes Potenzial für die empirische Sozialforschung.

Over the last decade, spin glass theory has turned from a fascinating part of t- oretical physics to a ?

Conjoint analysis (CA) and discrete choice experimentation (DCE) are tools used in marketing, economics, transportation, health, tourism, and other areas to develop and modify products, services, policies, and programs, specifically ones that can be described in terms of attributes.

The new edition adds a chapter on multiple linear regression in biomedical research, with sections including the multiple linear regressions model and least squares; the ANOVA table, parameter estimates, and confidence intervals; partial f-tests; polynomial regression; and analysis of covariance.

One of Riskbook.

This book deals with selected problems of machine perception, using various 2D and 3D imaging sensors.