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Statistical Inference Based on the likelihood
The Likelihood plays a key role in both introducing general notions of statistical theory, and in developing specific methods. This book introduces likelihood-based statistical theory and related methods from a classical viewpoint, and demonstrates how the main body of currently used statistical techniques can be generated from a few key concepts, in particular the likelihood. Focusing on those methods, which have both a solid theoretical background and practical relevance, the author gives formal justification of the methods used and provides numerical examples with real data.
The Skew-Normal and Related Families
The standard resource for statisticians and applied researchers. Accessible to the wide range of researchers who use statistical modelling techniques.
Data Analysis and Data Mining
An introduction to statistical data mining, Data Analysis and Data Mining is both textbook and professional resource. Assuming only a basic knowledge of statistical reasoning, it presents core concepts in data mining and exploratory statistical models to students and professional statisticians-both those working in communications and those working in a technological or scientific capacity-who have a limited knowledge of data mining. This book presents key statistical concepts by way of case studies, giving readers the benefit of learning from real problems and real data. Aided by a diverse range of statistical methods and techniques, readers will move from simple problems to complex problems...
Applied Smoothing Techniques for Data Analysis
The book describes the use of smoothing techniques in statistics, including both density estimation and nonparametric regression. Considerable advances in research in this area have been made in recent years. The aim of this text is to describe a variety of ways in which these methods can be applied to practical problems in statistics. The role of smoothing techniques in exploring data graphically is emphasised, but the use of nonparametric curves in drawing conclusions from data, as an extension of more standard parametric models, is also a major focus of the book. Examples are drawn from a wide range of applications. The book is intended for those who seek an introduction to the area, with...
Analyzing Spatial Models of Choice and Judgment with R
Modern Methods for Evaluating Your Social Science Data With recent advances in computing power and the widespread availability of political choice data, such as legislative roll call and public opinion survey data, the empirical estimation of spatial models has never been easier or more popular. Analyzing Spatial Models of Choice and Judgment with R demonstrates how to estimate and interpret spatial models using a variety of methods with the popular, open-source programming language R. Requiring basic knowledge of R, the book enables researchers to apply the methods to their own data. Also suitable for expert methodologists, it presents the latest methods for modeling the distances between p...
Compound Stress in English
This volume addresses several claims about the two prominence patterns found in English nominal compounds in a rigorously empirical way. Listener proficiency to identify these patterns is investigated, and the acoustic properties that distinguish the patterns are identified. These properties are used to predict statistically the prominence pattern of any given compound. The book further analyzes the semantic and structural factors influencing the distribution of the prominence patterns, and addresses the extent of within- and across-speaker variability in English compound stress assignment.
Elements of Computational Statistics
Will provide a more elementary introduction to these topics than other books available; Gentle is the author of two other Springer books
Innovation Diffusion Models
Innovation Diffusion Models Understand innovation diffusion models and their role in business success Innovation diffusion models are statistical models that predict the medium- and long-term sales performance of new products on a market. They account for numerous factors that contribute to the life cycle of a new product and are subject to continuous reassessment as markets transform and the business world becomes more complex. In a modern market environment where product life cycles are becoming ever shorter, the latest innovation diffusion models are essential for businesses looking to perfect their decision-making processes. Innovation Diffusion Models: Theory and Practice provides a com...
Computer Age Statistical Inference, Student Edition
Now in paperback and fortified with exercises, this brilliant, enjoyable text demystifies data science, statistics and machine learning.
Connectivity Prediction in Mobile Ad Hoc Networks for Real-Time Control
Cyber-physical systems are the next step in realizing the centuries old ubiquitous computing idea by focusing on open real-time systems design and device connectivity. Mobile ad hoc networks offer the flexible, local connectivity that cyber-physical systems require, if the connectivity can be realized dependably. One aspect of the dependability is the prediction of connectivity in the mobile ad hoc network. The presented research contributes to the connectivity prediction in mobile ad hoc networks with moving network participants in two ways: It systematically analyses the influence of scenario parameters on a set of connectivity metrics and it proposes and evaluates three classes of prediction models for these metrics.
