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This classic textbook covers all aspects of risk theory in a practical way. It builds on from the late R.E. Beard's extremely popular book Risk Theory...Savoir plus
Object Oriented Data Analysis is a framework that facilitates inter-disciplinary research through new terminology for discussing the often many possib...Savoir plus
Kernel smoothing has greatly evolved since its inception to become an essential methodology in the data science tool kit for the 21st century. Its wid...Savoir plus
This monograph provides a careful review of the major statistical techniques used to analyze regression data with nonconstant variability and skewness...Savoir plus
The book gives an up-to-date account of various approaches availablefor the analysis of infectious disease data. Most of the methods havebeen develope...Savoir plus
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As the amount of information recorded and stored electronically grows ever larger, it becomes increasingly useful, if not essential, to develop better...Savoir plus
Clustering remains a vibrant area of research in statistics. Although there are many books on this topic, there are relatively few that are well found...Savoir plus
Model-Free Curve Estimation details the Fourier series approach to density estimation and explores how model-free technology can be expanded to deal w...Savoir plus
Longitudinal studies often incur several problems that challenge standard statistical methods for data analysis. These problems include non-ignorable ...Savoir plus
The state-space approach provides a formal framework where any result or procedure developed for a basic model can be seamlessly applied to a standard...Savoir plus
Stochastic Analysis for Gaussian Random Processes and Fields: With Applications presents Hilbert space methods to study deep analytic properties conne...Savoir plus
Simultaneous confidence bands enable more intuitive and detailed inference of regression analysis than the standard inferential methods of parameter e...Savoir plus
Absolute Risk: Methods and Applications in Clinical Management and Public Health provides theory and examples to demonstrate the importance of absolut...Savoir plus
Large observational studies involving research questions that require the measurement of several features on each individual arise in many fields incl...Savoir plus
Repeated measures data arise when the same characteristic is measured on each case or subject at several times or under several conditions. There is a...Savoir plus
Identifying the sources and measuring the impact of haphazard variations are important in any number of research applications, from clinical trials an...Savoir plus
The success of the first edition of Generalized Linear Models led to the updated Second Edition, which continues to provide a definitive unified, trea...Savoir plus
Statistical inference carries great significance in model building from both the theoretical and the applications points of view. Its applications to ...Savoir plus
This book presents a radically new approach to problems of evaluating and optimizing the performance of continuous-time stochastic systems. This appro...Savoir plus
Kernel smoothing refers to a general methodology for recovery of underlying structure in data sets.The basic principle is that local averaging or smoo...Savoir plus
Data-analytic approaches to regression problems, arising from many scientific disciplines are described in this book. The aim of these nonparametric m...Savoir plus
How can major corporations and governments more quickly and accurately detect and address cyberattacks on their networks? How can local authorities im...Savoir plus
Multi-State Survival Models for Interval-Censored Data introduces methods to describe stochastic processes that consist of transitions between states ...Savoir plus