Subjective Probability Models for Lifetimes


Book Description

Bayesian methods in reliability cannot be fully utilized and understood without full comprehension of the essential differences that exist between frequentist probability and subjective probability. Switching from the frequentist to the subjective approach requires that some fundamental concepts be rethought and suitably redefined. Subjective Probability Models for Lifetimes details those differences and clarifies aspects of subjective probability that have a direct influence on modeling and drawing inference from failure and survival data. In particular, within a framework of Bayesian theory, the author considers the effects of different levels of information in the analysis of the phenomena of positive and negative aging. The author coherently reviews and compares the various definitions and results concerning stochastic ordering, statistical dependence, reliability, and decision theory. He offers a detailed but accessible mathematical treatment of different aspects of probability distributions for exchangeable vectors of lifetimes that imparts a clear understanding of what the "probabilistic description of aging" really is, and why it is important to analyzing survival and failure data.




Subjective Probability Models for Lifetimes


Book Description

Bayesian methods in reliability cannot be fully utilized and understood without full comprehension of the essential differences that exist between frequentist probability and subjective probability. Switching from the frequentist to the subjective approach requires that some fundamental concepts be rethought and suitably redefined. Subjecti




Subjective Probability


Book Description

Sample Text







Studies in Subjective Probability


Book Description

Truth and probability; Foresight: its logical laws, its subjective sources; The bases of probability; Subjective probability as the measure of a non-measurable set; The elicitation of personal probabilities; Probability: beware of falsifications; Probable knowledge.




Subset Selection in Regression


Book Description

Originally published in 1990, the first edition of Subset Selection in Regression filled a significant gap in the literature, and its critical and popular success has continued for more than a decade. Thoroughly revised to reflect progress in theory, methods, and computing power, the second edition promises to continue that tradition. The author ha




Smoothing Splines


Book Description

A general class of powerful and flexible modeling techniques, spline smoothing has attracted a great deal of research attention in recent years and has been widely used in many application areas, from medicine to economics. Smoothing Splines: Methods and Applications covers basic smoothing spline models, including polynomial, periodic, spherical, t




Dynamic Prediction in Clinical Survival Analysis


Book Description

There is a huge amount of literature on statistical models for the prediction of survival after diagnosis of a wide range of diseases like cancer, cardiovascular disease, and chronic kidney disease. Current practice is to use prediction models based on the Cox proportional hazards model and to present those as static models for remaining lifetime a




Local Polynomial Modelling and Its Applications


Book Description

Data-analytic approaches to regression problems, arising from many scientific disciplines are described in this book. The aim of these nonparametric methods is to relax assumptions on the form of a regression function and to let data search for a suitable function that describes the data well. The use of these nonparametric functions with parametric techniques can yield very powerful data analysis tools. Local polynomial modeling and its applications provides an up-to-date picture on state-of-the-art nonparametric regression techniques. The emphasis of the book is on methodologies rather than on theory, with a particular focus on applications of nonparametric techniques to various statistical problems. High-dimensional data-analytic tools are presented, and the book includes a variety of examples. This will be a valuable reference for research and applied statisticians, and will serve as a textbook for graduate students and others interested in nonparametric regression.




Stereology for Statisticians


Book Description

Setting out the principles of stereology from a statistical viewpoint, this book focuses on both basic theory and practical implications. The authors discuss ways to effectively communicate statistical issues to clients, draw attention to common methodological errors, and provide references to essential literature. The first full text on design-based stereology opens with a review of classical and modern stereology, followed by a treatment of mathematical foundations and then on to core techniques. The final chapters discuss implementing techniques in practical sampling designs, summarize understanding of the variance of stereological estimators, and describe open problems for further research. The book also details isotropic, vertical or local sampling designs for estimating stereological parameters such as volume, surface area, particle number and spatial distribution. This extensive text offers support to statistical consultants using examples, applications and unique Advice to Consultants sections. It contains numerous literature references, bibliographic notes and nearly 150 illustrations.