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Weighted Empirical Processes in Dynamic Nonlinear Models
This book presents a unified approach for obtaining the limiting distributions of minimum distance. It discusses classes of goodness-of-t tests for fitting an error distribution in some of these models and/or fitting a regression-autoregressive function without assuming the knowledge of the error distribution. The main tool is the asymptotic equi-continuity of certain basic weighted residual empirical processes in the uniform and L2 metrics.
An Introduction to Copulas
Copulas are functions that join multivariate distribution functions to their one-dimensional margins. The study of copulas and their role in statistics is a new but vigorously growing field. In this book the student or practitioner of statistics and probability will find discussions of the fundamental properties of copulas and some of their primary applications. The applications include the study of dependence and measures of association, and the construction of families of bivariate distributions. With nearly a hundred examples and over 150 exercises, this book is suitable as a text or for self-study. The only prerequisite is an upper level undergraduate course in probability and mathematical statistics, although some familiarity with nonparametric statistics would be useful. Knowledge of measure-theoretic probability is not required. Roger B. Nelsen is Professor of Mathematics at Lewis & Clark College in Portland, Oregon. He is also the author of "Proofs Without Words: Exercises in Visual Thinking," published by the Mathematical Association of America.
Weak Dependence: With Examples and Applications
This book develops Doukhan/Louhichi's 1999 idea to measure asymptotic independence of a random process. The authors, who helped develop this theory, propose examples of models fitting such conditions: stable Markov chains, dynamical systems or more complicated models, nonlinear, non-Markovian, and heteroskedastic models with infinite memory. Applications are still needed to develop a method of analysis for nonlinear times series, and this book provides a strong basis for additional studies.
Computation of Multivariate Normal and t Probabilities
Multivariate normal and t probabilities are needed for statistical inference in many applications. Modern statistical computation packages provide functions for the computation of these probabilities for problems with one or two variables. This book describes recently developed methods for accurate and efficient computation of the required probability values for problems with two or more variables. The book discusses methods for specialized problems as well as methods for general problems. The book includes examples that illustrate the probability computations for a variety of applications.
Multivariate Nonparametric Methods with R
This book offers a new, fairly efficient, and robust alternative to analyzing multivariate data. The analysis of data based on multivariate spatial signs and ranks proceeds very much as does a traditional multivariate analysis relying on the assumption of multivariate normality; the regular L2 norm is just replaced by different L1 norms, observation vectors are replaced by spatial signs and ranks, and so on. A unified methodology starting with the simple one-sample multivariate location problem and proceeding to the general multivariate multiple linear regression case is presented. Companion estimates and tests for scatter matrices are considered as well. The R package MNM is available for c...
National Patterns of R&D Resources
National Patterns of R&D Resources is an annual report issued by the National Center for Science and Engineering Statistics (NCSES) of the National Science Foundation, which provides a national view of current 'patterns' in funding of R&D activities in government, industry, academia, federally funded research and development centers, and non-profits. Total R&D funds are broken out at the national level by type of provider, type of recipient, and whether the R&D is basic, applied, or developmental. These patterns are compared both longitudinally versus historical R&D amounts, and internationally. This report series, which is based on input from several censuses and surveys, is used to formula...
Medical Care Economic Risk
The United States has seen major advances in medical care during the past decades, but access to care at an affordable cost is not universal. Many Americans lack health care insurance of any kind, and many others with insurance are nonetheless exposed to financial risk because of high premiums, deductibles, co-pays, limits on insurance payments, and uncovered services. One might expect that the U.S. poverty measure would capture these financial effects and trends in them over time. Yet the current official poverty measure developed in the early 1960s does not take into account significant increases and variations in medical care costs, insurance coverage, out-of-pocket spending, and the fina...
Communicating Science and Engineering Data in the Information Age
The National Center for Science and Engineering Statistics (NCSES) of the National Science Foundation (NSF) communicates its science and engineering (S&E) information to data users in a very fluid environment that is undergoing modernization at a pace at which data producer dissemination practices, protocols, and technologies, on one hand, and user demands and capabilities, on the other, are changing faster than the agency has been able to accommodate. NCSES asked the Committee on National Statistics and the Computer Science and Telecommunications Board of the National Research Council to form a panel to review the NCSES communication and dissemination program that is concerned with the coll...
Rationalizing Rural Area Classifications for the Economic Research Service
The U.S. Department of Agriculture Economic Research Service (USDA/ERS) maintains four highly related but distinct geographic classification systems to designate areas by the degree to which they are rural. The original urban-rural code scheme was developed by the ERS in the 1970s. Rural America today is very different from the rural America of 1970 described in the first rural classification report. At that time migration to cities and poverty among the people left behind was a central concern. The more rural a residence, the more likely a person was to live in poverty, and this relationship held true regardless of age or race. Since the 1970s the interstate highway system was completed and...
Nonparametric Goodness-of-Fit Testing Under Gaussian Models
This book presents the modern theory of nonparametric goodness-of-fit testing. It fills the gap in modern nonparametric statistical theory by discussing hypothesis testing and addresses mathematical statisticians who are interesting in the theory of non-parametric statistical inference. It will be of interest to specialists who are dealing with applied non-parametric statistical problems relevant in signal detection and transmission and in technical and medical diagnostics among others.
