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Author: Pavel S. Knopov Publisher: Springer Science & Business Media ISBN: 1461405742 Category : Business & Economics Languages : en Pages : 245
Book Description
This monograph focuses on the construction of regression models with linear and non-linear constrain inequalities from the theoretical point of view. Unlike previous publications, this volume analyses the properties of regression with inequality constrains, investigating the flexibility of inequality constrains and their ability to adapt in the presence of additional a priori information The implementation of inequality constrains improves the accuracy of models, and decreases the likelihood of errors. Based on the obtained theoretical results, a computational technique for estimation and prognostication problems is suggested. This approach lends itself to numerous applications in various practical problems, several of which are discussed in detail The book is useful resource for graduate students, PhD students, as well as for researchers who specialize in applied statistics and optimization. This book may also be useful to specialists in other branches of applied mathematics, technology, econometrics and finance
Author: Pavel S. Knopov Publisher: Springer Science & Business Media ISBN: 1461405742 Category : Business & Economics Languages : en Pages : 245
Book Description
This monograph focuses on the construction of regression models with linear and non-linear constrain inequalities from the theoretical point of view. Unlike previous publications, this volume analyses the properties of regression with inequality constrains, investigating the flexibility of inequality constrains and their ability to adapt in the presence of additional a priori information The implementation of inequality constrains improves the accuracy of models, and decreases the likelihood of errors. Based on the obtained theoretical results, a computational technique for estimation and prognostication problems is suggested. This approach lends itself to numerous applications in various practical problems, several of which are discussed in detail The book is useful resource for graduate students, PhD students, as well as for researchers who specialize in applied statistics and optimization. This book may also be useful to specialists in other branches of applied mathematics, technology, econometrics and finance
Author: Calyampudi Radhakrishna Rao Publisher: Taylor & Francis ISBN: 9788122412857 Category : Mathematical statistics Languages : en Pages : 520
Book Description
The Volume Five Of Selected Papers Of C.R. Rao Consists Of 32 Papers That Appeared In Various Publications From 1985. These Papers Are Selected To Showcase Some Of The Fundamental Contributions In Characterizations Of Probability Distributions, Density Estimation, Analysis Of Multivariate Familial Data, Correspondence Analysis, Shape And Size Analysis, Signal Detection, Inference Based On Quadratic Entropy, Bootstrap, L-L Norm, Convex Discrepancy Function Etc., Estimation Problems In Univariate And Multivariate Linear Models And Regression Models Using Unified Theory Of Linear Estimation, M-Estimates, Lad Estimates Etc. And Many More Novel Concepts And Ideas With Enormous Potential For Further Research And In Which Active Research Is Being Carried Out.The Highlight Of This Volume Is The Stimulating Retrospection Of Prof. C.R. Rao About His Work Spanning The Last Three Score Years. An Updated Bibliography And A Brief Biographical Profile Of Prof. Rao Are Also Included.These Volumes Are Intended Not Only As A Ready Reference To Most Of Prof. Rao'S Oft Quoted And Used Results But Also To Inspire And Initiate Research Workers To The Broad Spectrum Of Areas In Theoretical And Applied Statistics In Which Prof. Rao Has Contributed.
Author: Ze Pei Jiang Publisher: World Scientific ISBN: 9814555290 Category : Languages : en Pages : 322
Book Description
The main topics covered in this proceedings include: Interacting Particle Systems, Markov Processes and Potential Theory, Random Fields, Stochastic Analysis, Large Deviation Theory, Fractals and Superprocesses; Nonparametric Analysis, Robust Analysis, Multivariate Analysis, The Projection Pursuit, The Jackknife, Time Series, Linear Model, Regression and Limit Theorems.
Author: Rene Gonin Publisher: Routledge ISBN: 1351428179 Category : Mathematics Languages : en Pages : 318
Book Description
Complete with valuable FORTRAN programs that help solve nondifferentiable nonlinear LtandLo.-norm estimation problems, this important reference/text extensively delineates ahistory of Lp-norm estimation. It examines the nonlinear Lp-norm estimation problem that isa viable alternative to least squares estimation problems where the underlying errordistribution is nonnormal, i.e., non-Gaussian.Nonlinear LrNorm Estimation addresses both computational and statistical aspects ofLp-norm estimation problems to bridge the gap between these two fields . . . contains 70useful illustrations ... discusses linear Lp-norm as well as nonlinear Lt, Lo., and Lp-normestimation problems . . . provides all appropriate computational algorithms and FORTRANlistings for nonlinear Lt- and Lo.-norm estimation problems . . . guides readers with clear endof-chapter notes on related topics and outstanding research publications . . . contains numericalexamples plus several practical problems .. . and shows how the data can prescribe variousapplications of Lp-norm alternatives.Nonlinear Lp-Norm Estimation is an indispensable reference for statisticians,operations researchers, numerical analysts, applied mathematicians, biometricians, andcomputer scientists, as well as a text for graduate students in statistics or computer science.
Author: Zehua Chen Publisher: World Scientific ISBN: 9814471755 Category : Mathematics Languages : en Pages : 397
Book Description
This book, which is split into two parts, is about Prof. Zhidong Bai's life and his contributions to statistics and probability. The first part contains an interview with Zhidong Bai conducted by Dr Atanu Biswas from the Indian Statistical Institute, and seven short articles detailing Bai's contributions. The second part is a collection of his selected seminal papers in the areas of random matrix theory, Edgeworth expansion, M-estimation, model selection, adaptive design in clinical trials, applied probability in algorithms, small area estimation, and time series, among others. This book provides an easy access to Zhidong Bai's important works, and serves as a useful reference for researchers who are working in the relevant areas.
Author: C. Radhakrishna Rao Publisher: Springer Science & Business Media ISBN: 3540742271 Category : Mathematics Languages : en Pages : 583
Book Description
Revised and updated with the latest results, this Third Edition explores the theory and applications of linear models. The authors present a unified theory of inference from linear models and its generalizations with minimal assumptions. They not only use least squares theory, but also alternative methods of estimation and testing based on convex loss functions and general estimating equations. Highlights of coverage include sensitivity analysis and model selection, an analysis of incomplete data, an analysis of categorical data based on a unified presentation of generalized linear models, and an extensive appendix on matrix theory.
Author: Zehua Chen Publisher: World Scientific ISBN: 9812793089 Category : Biography & Autobiography Languages : en Pages : 397
Book Description
This book, which is split into two parts, is about Prof. Zhidong Bai's life and his contributions to statistics and probability. The first part contains an interview with Zhidong Bai conducted by Dr Atanu Biswas from the Indian Statistical Institute, and seven short articles detailing Bai's contributions. The second part is a collection of his selected seminal papers in the areas of random matrix theory, Edgeworth expansion, M-estimation, model selection, adaptive design in clinical trials, applied probability in algorithms, small area estimation, and time series, among others. This book provides an easy access to Zhidong Bai's important works, and serves as a useful reference for researchers who are working in the relevant areas.
Author: C.Radhakrishna Rao Publisher: Springer Science & Business Media ISBN: 1489900241 Category : Mathematics Languages : en Pages : 360
Book Description
The book is based on both authors' several years of experience in teaching linear models at various levels. It gives an up-to-date account of the theory and applications of linear models. The book can be used as a text for courses in statistics at the graduate level and as an accompanying text for courses in other areas. Some of the highlights in this book are as follows. A relatively extensive chapter on matrix theory (Appendix A) provides the necessary tools for proving theorems discussed in the text and offers a selection of classical and modern algebraic results that are useful in research work in econometrics, engineering, and optimization theory. The matrix theory of the last ten years has produced a series of fundamental results about the definiteness of matrices, especially for the differences of matrices, which enable superiority comparisons of two biased estimates to be made for the first time. We have attempted to provide a unified theory of inference from linear models with minimal assumptions. Besides the usual least-squares theory, alternative methods of estimation and testing based on convex loss func tions and general estimating equations are discussed. Special emphasis is given to sensitivity analysis and model selection. A special chapter is devoted to the analysis of categorical data based on logit, loglinear, and logistic regression models. The material covered, theoretical discussion, and its practical applica tions will be useful not only to students but also to researchers and con sultants in statistics.
Author: Calyampudi R. Rao Publisher: Springer Science & Business Media ISBN: 0387227520 Category : Mathematics Languages : en Pages : 439
Book Description
An up-to-date account of the theory and applications of linear models, for use as a textbook in statistics at graduate level as well as an accompanying text for other courses in which linear models play a part. The authors present a unified theory of inference from linear models with minimal assumptions, not only through least squares theory, but also using alternative methods of estimation and testing based on convex loss functions and general estimating equations. Highlights include: - a special emphasis on sensitivity analysis and model selection; - a chapter devoted to the analysis of categorical data based on logic, loglinear, and logistic regression models; - a chapter devoted to incomplete data sets; - an extensive appendix on matrix theory; - a chapter devoted to the analysis of categorical data based on a unified presentation of generalized linear models including GEE-methods for correlated response; - a chapter devoted to incomplete data sets including regression diagnostics to identify Non-MCAR-processes The material covered is thus invaluable not only to graduates, but also to researchers and consultants in statistics.
Author: Pavel S. Knopov
Author: Pavel S. Knopov
Author: Calyampudi Radhakrishna Rao
Author: Ze Pei Jiang
Author: Rene Gonin
Author: Zehua Chen
Author: C. Radhakrishna Rao
Author: Zehua Chen
Author: C.Radhakrishna Rao
Author: Calyampudi R. Rao
Author: