Author: Hira L. KoulPublisher: IMS
ISBN: 9780940600287
Category : Autoregression (Statistics).
Languages : en
Pages : 286
Book Description
Weighted Empiricals and Linear Models
Author: Hira L. KoulPublisher: IMS
ISBN: 9780940600287
Category : Autoregression (Statistics).
Languages : en
Pages : 286
Book Description
Weighted Empirical Processes in Dynamic Nonlinear Models
Author: Hira L. KoulPublisher: Springer Science & Business Media
ISBN: 9780387954769
Category : Mathematics
Languages : en
Pages : 454
Book Description
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.
Weighted Empirical Processes in Dynamic Nonlinear Models
Author: Hira L. KoulPublisher: Springer Science & Business Media
ISBN: 146130055X
Category : Mathematics
Languages : en
Pages : 444
Book Description
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.
Advance Data from Vital and Health Statistics
Author: Robust Statistical Procedures
Author: Jana JureckováPublisher: John Wiley & Sons
ISBN: 9780471822219
Category : Mathematics
Languages : en
Pages : 496
Book Description
A broad and unified methodology for robust statistics—with exciting new applications Robust statistics is one of the fastest growing fields in contemporary statistics. It is also one of the more diverse and sometimes confounding areas, given the many different assessments and interpretations of robustness by theoretical and applied statisticians. This innovative book unifies the many varied, yet related, concepts of robust statistics under a sound theoretical modulation. It seamlessly integrates asymptotics and interrelations, and provides statisticians with an effective system for dealing with the interrelations between the various classes of procedures. Drawing on the expertise of researchers from around the world, and covering over a decade's worth of developments in the field, Robust Statistical Procedures: Asymptotics and Interrelations: Discusses both theory and applications in its two parts, from the fundamentals to robust statistical inference Thoroughly explores the interrelations between diverse classes of procedures, unlike any other book Compares nonparametric procedures with robust statistics, explaining in detail asymptotic representations for various estimators Provides a timesaving list of mathematical tools for the problems under discussion Keeps mathematical abstractions to a minimum, in spite of its largely theoretical content Includes useful problems and exercises at the end of each chapter Offers strategies for more complex models when using robust statistical procedures Self-contained and rounded in approach, this book is invaluable for both applied statisticians and theoretical researchers; for graduate students in mathematical statistics; and for anyone interested in the influence of this methodology.
Empirical Bayes and Likelihood Inference
Author: S.E. AhmedPublisher: Springer Science & Business Media
ISBN: 1461301416
Category : Mathematics
Languages : en
Pages : 242
Book Description
Bayesian and such approaches to inference have a number of points of close contact, especially from an asymptotic point of view. Both emphasize the construction of interval estimates of unknown parameters. In this volume, researchers present recent work on several aspects of Bayesian, likelihood and empirical Bayes methods, presented at a workshop held in Montreal, Canada. The goal of the workshop was to explore the linkages among the methods, and to suggest new directions for research in the theory of inference.
Large Sample Inference For Long Memory Processes
Author: Donatas SurgailisPublisher: World Scientific Publishing Company
ISBN: 1911299387
Category : Mathematics
Languages : en
Pages : 594
Book Description
Box and Jenkins (1970) made the idea of obtaining a stationary time series by differencing the given, possibly nonstationary, time series popular. Numerous time series in economics are found to have this property. Subsequently, Granger and Joyeux (1980) and Hosking (1981) found examples of time series whose fractional difference becomes a short memory process, in particular, a white noise, while the initial series has unbounded spectral density at the origin, i.e. exhibits long memory.Further examples of data following long memory were found in hydrology and in network traffic data while in finance the phenomenon of strong dependence was established by dramatic empirical success of long memory processes in modeling the volatility of the asset prices and power transforms of stock market returns.At present there is a need for a text from where an interested reader can methodically learn about some basic asymptotic theory and techniques found useful in the analysis of statistical inference procedures for long memory processes. This text makes an attempt in this direction. The authors provide in a concise style a text at the graduate level summarizing theoretical developments both for short and long memory processes and their applications to statistics. The book also contains some real data applications and mentions some unsolved inference problems for interested researchers in the field./a
Frontiers in Statistics
Author: Jianqing FanPublisher: Imperial College Press
ISBN: 186094888X
Category : Mathematics
Languages : en
Pages : 552
Book Description
During the last two decades, many areas of statistical inference have experienced phenomenal growth. This book presents a timely analysis and overview of some of these new developments and a contemporary outlook on the various frontiers of statistics.Eminent leaders in the field have contributed 16 review articles and 6 research articles covering areas including semi-parametric models, data analytical nonparametric methods, statistical learning, network tomography, longitudinal data analysis, financial econometrics, time series, bootstrap and other re-sampling methodologies, statistical computing, generalized nonlinear regression and mixed effects models, martingale transform tests for model diagnostics, robust multivariate analysis, single index models and wavelets.This volume is dedicated to Prof. Peter J Bickel in honor of his 65th birthday. The first article of this volume summarizes some of Prof. Bickel''s distinguished contributions.
A FORTRAN Program for Determining an Empirical Expression for a Quantity Measured at Combinations of Several Levels of Each of Two Variables
Author: Mary Nan SteelPublisher:
ISBN:
Category : Computer programming
Languages : en
Pages : 68
Book Description
This note relates to a general procedure, reported elsewhere, for finding an empirical expression for the functional dependence of a measured quantity on two variables.The procedure is applicable when measurements of the dependent variable are available at m * .n combinations of m levels of one variable and n levels of the other; it leads to an algebraic expression relating the three variables.A Fortran program to perform the various steps of the general procedure is presented along with detailed instructions for its use.The program also includes the calculation of an analysis of variance, of components of variance, of significance tests, tables of residuals, and a number of other quantities.(Author).
Geographically Weighted Regression
Author: A. Stewart FotheringhamPublisher: John Wiley & Sons
ISBN: 0470855258
Category : Science
Languages : en
Pages : 282
Book Description
Geographical Weighted Regression (GWR) is a new local modelling technique for analysing spatial analysis. This technique allows local as opposed to global models of relationships to be measured and mapped. This is the first and only book on this technique, offering comprehensive coverage on this new 'hot' topic in spatial analysis. * Provides step-by-step examples of how to use the GWR model using data sets and examples on issues such as house price determinants, educational attainment levels and school performance statistics * Contains a broad discussion of and basic concepts on GWR through to ideas on statistical inference for GWR models * uniquely features accompanying author-written software that allows users to undertake sophisticated and complex forms of GWR within a user-friendly, Windows-based, front-end (see book for details).