Statistical Data Analysis Based On The L1 Norm And Related Methods
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Statistical Data Analysis Based on the L1-Norm and Related Methods by Yadolah Dodge Pdf
This volume contains a selection of invited papers, presented to the fourth International Conference on Statistical Data Analysis Based on the L1-Norm and Related Methods, held in Neuchâtel, Switzerland, from August 4–9, 2002. The contributions represent clear evidence to the importance of the development of theory, methods and applications related to the statistical data analysis based on the L1-norm.
Statistical Data Analysis Based on the L1-norm and Related Methods by Yadolah Dodge Pdf
This volume contains a selection of invited papers, presented to the fourth International Conference on Statistical Data Analysis Based on the L1-Norm and Related Methods, held in NeuchA[tel, Switzerland, from August 4a "9, 2002. The contributions represent a clear evidence to the importance of development of theory, methods and applications related to the statistical data analysis based on the L1-norm.
L1-statistical Analysis and Related Methods by Yadolah Dodge Pdf
Presented in this volume are recent results obtained in statistical analysis based on the L 1 -norm and related methods. The volume demonstrates new trends and directions in the field, and confirms the well-foundedness of the topic. The book will appeal to statisticians and research workers in all areas of applied sciences. It will also serve as a reference or a complementary text book in universities.
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.
New Approaches in Classification and Data Analysis by Edwin Diday,Yves Lechevallier,Martin Schader,Patrice Bertrand,Bernard Burtschy Pdf
The subject of this book is the analysis and processing of structural or quantitative data with emphasis on classification methods, new algorithms as well as applications in various fields related to data analysis and classification. The book presents the state of the art in world-wide research and application of methods from the fields indicated above and consists of survey papers as well as research papers.
L1-Norm and L∞-Norm Estimation by Richard Farebrother Pdf
This monograph is concerned with the fitting of linear relationships in the context of the linear statistical model. As alternatives to the familiar least squared residuals procedure, it investigates the relationships between the least absolute residuals, the minimax absolute residual and the least median of squared residuals procedures. It is intended for graduate students and research workers in statistics with some command of matrix analysis and linear programming techniques.
Advances in Statistics by Zehua Chen,Jin-Ting Zhang,Feifang Hu Pdf
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.
Mathematical Programming and Game Theory for Decision Making by S. K. Neogy Pdf
This edited book presents recent developments and state-of-the-art review in various areas of mathematical programming and game theory. It is a peer-reviewed research monograph under the ISI Platinum Jubilee Series on Statistical Science and Interdisciplinary Research. This volume provides a panoramic view of theory and the applications of the methods of mathematical programming to problems in statistics, finance, games and electrical networks. It also provides an important as well as timely overview of research trends and focuses on the exciting areas like support vector machines, bilevel programming, interior point method for convex quadratic programming, cooperative games, non-cooperative games and stochastic games. Researchers, professionals and advanced graduates will find the book an essential resource for current work in mathematical programming, game theory and their applications. Sample Chapter(s). Foreword (45 KB). Chapter 1: Mathematical Programming and its Applications in Finance (177 KB). Contents: Mathematical Programming and Its Applications in Finance (L C Thomas); Anti-Stalling Pivot Rule for Linear Programs with Totally Unimodular Coefficient Matrix (S N Kabadi & A P Punnen); A New Practically Efficient Interior Point Method for Convex Quadratic Programming (K G Murty); A General Framework for the Analysis of Sets of Constraints (R Caron & T Traynor), Tolerance-Based Algorithms for the Traveling Salesman Problem (D Ghosh et al.); On the Membership Problem of the Pedigree Polytope (T S Arthanari); Exact Algorithms for a One-Defective Vertex Colouring Problem (N Achuthan et al.); Complementarity Problem Involving a Vertical Block Matrix and Its Solution Using Neural Network Model (S K Neogy et al.); Fuzzy Twin Support Vector Machines for Pattern Classification (R Khemchandani et al.); An Overview of the Minimum Sum of Absolute Errors Regression (S C Narula & J F Wellington); Hedging Against the Market with No Short Selling (S A Clark & C Srinivasan); Mathematical Programming and Electrical Network Analysis II: Computational Linear Algebra Through Network Analysis (H Narayanan); Dynamic Optimal Control Policy in Price and Quality for High Technology Product (A K Bardhan & U Chanda); Forecasting for Supply Chain and Portfolio Management (K G Murty); Variational Analysis in Bilevel Programming (S Dempe et al.); Game Engineering (R J Aumann); Games of Connectivity (P Dubey & R Garg); A Robust Feedback Nash Equilibrium in a Climate Change Policy Game (M Hennlock); De Facto Delegation and Proposer Rules (H Imai & K Yonezaki); The Bargaining Set in Effectivity Function (D Razafimahatolotra); Dynamic Oligopoly as a Mixed Large Game OCo Toy Market (A Wiszniewska-Matyszkiel); On Some Classes of Balanced Games (R B Bapat); Market Equilibrium for Combinatorial Auctions and the Matching Core of Nonnegative TU Games (S Lahiri); Continuity, Manifolds, and Arrow''s Social Choice Problem (K Saukkonen); On a Mixture Class of Stochastic Games with Ordered Field Property (S K Neogy). Readership: Researchers, professionals and advanced students in mathematical programming, game theory, management sciences and computational mathematics.
Selected Papers of C.R. Rao by Calyampudi Radhakrishna Rao Pdf
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.
Alternative Methods of Regression by David Birkes,Dr. Yadolah Dodge Pdf
Of related interest. Nonlinear Regression Analysis and its Applications Douglas M. Bates and Donald G. Watts ".an extraordinary presentation of concepts and methods concerning the use and analysis of nonlinear regression models.highly recommend[ed].for anyone needing to use and/or understand issues concerning the analysis of nonlinear regression models." --Technometrics This book provides a balance between theory and practice supported by extensive displays of instructive geometrical constructs. Numerous in-depth case studies illustrate the use of nonlinear regression analysis--with all data sets real. Topics include: multi-response parameter estimation; models defined by systems of differential equations; and improved methods for presenting inferential results of nonlinear analysis. 1988 (0-471-81643-4) 365 pp. Nonlinear Regression G. A. F. Seber and C. J. Wild ".[a] comprehensive and scholarly work.impressively thorough with attention given to every aspect of the modeling process." --Short Book Reviews of the International Statistical Institute In this introduction to nonlinear modeling, the authors examine a wide range of estimation techniques including least squares, quasi-likelihood, and Bayesian methods, and discuss some of the problems associated with estimation. The book presents new and important material relating to the concept of curvature and its growing role in statistical inference. It also covers three useful classes of models --growth, compartmental, and multiphase --and emphasizes the limitations involved in fitting these models. Packed with examples and graphs, it offers statisticians, statistical consultants, and statistically oriented research scientists up-to-date access to their fields. 1989 (0-471-61760-1) 768 pp. Mathematical Programming in Statistics T. S. Arthanari and Yadolah Dodge "The authors have achieved their stated intention.in an outstanding and useful manner for both students and researchers.Contains a superb synthesis of references linked to the special topics and formulations by a succinct set of bibliographical notes.Should be in the hands of all system analysts and computer system architects." --Computing Reviews This unique book brings together most of the available results on applications of mathematical programming in statistics, and also develops the necessary statistical and programming theory and methods. 1981 (0-471-08073-X) 413 pp.
Kenneth J. Berry,Janis E. Johnston,Paul W. Mielke Jr.
Author : Kenneth J. Berry,Janis E. Johnston,Paul W. Mielke Jr. Publisher : Springer Science & Business Media Page : 517 pages File Size : 48,8 Mb Release : 2014-04-11 Category : Mathematics ISBN : 9783319027449
A Chronicle of Permutation Statistical Methods by Kenneth J. Berry,Janis E. Johnston,Paul W. Mielke Jr. Pdf
The focus of this book is on the birth and historical development of permutation statistical methods from the early 1920s to the near present. Beginning with the seminal contributions of R.A. Fisher, E.J.G. Pitman, and others in the 1920s and 1930s, permutation statistical methods were initially introduced to validate the assumptions of classical statistical methods. Permutation methods have advantages over classical methods in that they are optimal for small data sets and non-random samples, are data-dependent, and are free of distributional assumptions. Permutation probability values may be exact, or estimated via moment- or resampling-approximation procedures. Because permutation methods are inherently computationally-intensive, the evolution of computers and computing technology that made modern permutation methods possible accompanies the historical narrative. Permutation analogs of many well-known statistical tests are presented in a historical context, including multiple correlation and regression, analysis of variance, contingency table analysis, and measures of association and agreement. A non-mathematical approach makes the text accessible to readers of all levels.
Methods of Microarray Data Analysis III by Kimberly F. Johnson,Simon M. Lin Pdf
As microarray technology has matured, data analysis methods have advanced as well. Methods Of Microarray Data Analysis III is the third book in this pioneering series dedicated to the existing new field of microarrays. While initial techniques focused on classification exercises (volume I of this series), and later on pattern extraction (volume II of this series), this volume focuses on data quality issues. Problems such as background noise determination, analysis of variance, and errors in data handling are highlighted. Three tutorial papers are presented to assist with a basic understanding of underlying principles in microarray data analysis, and twelve new papers are highlighted analyzing the same CAMDA'02 datasets: the Project Normal data set or the Affymetrix Latin Square data set. A comparative study of these analytical methodologies brings to light problems, solutions and new ideas. This book is an excellent reference for academic and industrial researchers who want to keep abreast of the state of art of microarray data analysis.
Linear Models and Generalizations by C. Radhakrishna Rao,Helge Toutenburg,Shalabh,Christian Heumann Pdf
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.
