Proceedings Of The International Conference On Linear Statistical Inference

Author : Tadeusz Calinski,Radoslaw Kala
Publisher : Springer Science & Business Media
Page : 309 pages
File Size : 40,9 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9789401110044

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Proceedings of the International Conference on Linear Statistical Inference LINSTAT ’93 by Tadeusz Calinski,Radoslaw Kala Pdf

The International Conference on Linear Statistical Inference LINSTAT'93 was held in Poznan, Poland, from May 31 to June 4, 1993. The purpose of the confer ence was to enable scientists, from various countries, engaged in the diverse areas of statistical sciences and practice to meet together and exchange views and re sults related to the current research on linear statistical inference in its broadest sense. Thus, the conference programme included sessions on estimation, prediction and testing in linear models, on robustness of some relevant statistical methods, on estimation of variance components appearing in linear models, on certain gen eralizations to nonlinear models, on design and analysis of experiments, including optimality and comparison of linear experiments, and on some other topics related to linear statistical inference. Within the various sessions 22 invited papers and 37 contributed papers were presented, 12 of them as posters. The conference gathered 94 participants from eighteen countries of Europe, North America and Asia. There were 53 participants from abroad and 41 from Poland. The conference was the second of this type, devoted to linear statistical inference. The first was held in Poznan in June, 4-8, 1984. Both belong to the series of confer ences on mathematical statistics and probability theory organized under the auspices of the Committee of Mathematics of the Polish Academy of Sciences, due to the ini tiative and efforts of its Mathematical Statistics Section. In the years 1973-1993 there were held in Poland nineteen such conferences, some of them international.

Author : T. Calinski,W. Klonecki
Publisher : Springer Science & Business Media
Page : 326 pages
File Size : 46,7 Mb
Release : 2013-03-09
Category : Mathematics
ISBN : 9781461573531

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Linear Statistical Inference by T. Calinski,W. Klonecki Pdf

An International Statistical Conference on Linear Inference was held in Poznan, Poland, on June 4-8, 1984. The conference was organized under the auspices of the Polish Section of the Bernoulli Society, the Committee of Mathematical Sciences and the Mathematical Institute of the ,Polish Academy of Sciences. The purpose of the meeting was to bring together scientists from vari ous countries working in the diverse areas of statistical sciences but showing great interest in the advances of research on linear inference taken in its broad sense. Thus, the conference programme included ses sions on Gauss-Markov models, robustness, variance components~ experi mental design, multiple comparisons, multivariate models, computational aspects and on some special topics. 38 papers were read within the vari ous sessions and 5 were presented as posters. At the end of the confer ence a lively general discussion session was held. The conference gathered more than ninety participants from 16 countries, representing both parts of Europe, North America and Asia. Judging from opinions expressed by many participants, the conference was quite suc cessful, well contributing to the dissemination of knowledge and the stimulation of research in different areas linked with statistical li near inference. If the conference was really a success, it was due to all its participants who in various ways were devoting their time and efforts to make the conference fruitful and enjoyable.

Author : Witold Klonecki,T. Caliński
Publisher : Unknown
Page : 320 pages
File Size : 42,7 Mb
Release : 1985
Category : Linear models (Statistics)
ISBN : OCLC:1329090021

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Linear Statistical Inference by Witold Klonecki,T. Caliński Pdf

An International Statistical Conference on Linear Inference was held in Poznan, Poland, on June 4-8, 1984. The conference was organized under the auspices of the Polish Section of the Bernoulli Society, the Committee of Mathematical Sciences and the Mathematical Institute of the ,Polish Academy of Sciences. The purpose of the meeting was to bring together scientists from vari ous countries working in the diverse areas of statistical sciences but showing great interest in the advances of research on linear inference taken in its broad sense. Thus, the conference programme included ses sions on Gauss-Markov models, robustness, variance components~ experi mental design, multiple comparisons, multivariate models, computational aspects and on some special topics. 38 papers were read within the vari ous sessions and 5 were presented as posters. At the end of the confer ence a lively general discussion session was held. The conference gathered more than ninety participants from 16 countries, representing both parts of Europe, North America and Asia. Judging from opinions expressed by many participants, the conference was quite suc cessful, well contributing to the dissemination of knowledge and the stimulation of research in different areas linked with statistical li near inference. If the conference was really a success, it was due to all its participants who in various ways were devoting their time and efforts to make the conference fruitful and enjoyable.

Author : T. Calinski,W. Klonecki
Publisher : Unknown
Page : 328 pages
File Size : 44,8 Mb
Release : 2014-01-15
Category : Electronic
ISBN : 1461573548

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Linear Statistical Inference by T. Calinski,W. Klonecki Pdf

Author : C. Radhakrishna Rao
Publisher : John Wiley & Sons
Page : 656 pages
File Size : 51,5 Mb
Release : 2009-09-25
Category : Mathematics
ISBN : 9780470317143

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Linear Statistical Inference and its Applications by C. Radhakrishna Rao Pdf

"C. R. Rao would be found in almost any statistician's list of five outstanding workers in the world of Mathematical Statistics today. His book represents a comprehensive account of the main body of results that comprise modern statistical theory." -W. G. Cochran "[C. R. Rao is] one of the pioneers who laid the foundations of statistics which grew from ad hoc origins into a firmly grounded mathematical science." -B. Efrom Translated into six major languages of the world, C. R. Rao's Linear Statistical Inference and Its Applications is one of the foremost works in statistical inference in the literature. Incorporating the important developments in the subject that have taken place in the last three decades, this paperback reprint of his classic work on statistical inference remains highly applicable to statistical analysis. Presenting the theory and techniques of statistical inference in a logically integrated and practical form, it covers: * The algebra of vectors and matrices * Probability theory, tools, and techniques * Continuous probability models * The theory of least squares and the analysis of variance * Criteria and methods of estimation * Large sample theory and methods * The theory of statistical inference * Multivariate normal distribution Written for the student and professional with a basic knowledge of statistics, this practical paperback edition gives this industry standard new life as a key resource for practicing statisticians and statisticians-in-training.

Author : Yoel Haitovsky,Hans Rudolf Lerche,Ya'acov Ritov
Publisher : Springer Science & Business Media
Page : 230 pages
File Size : 52,7 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9783642574108

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Foundations of Statistical Inference by Yoel Haitovsky,Hans Rudolf Lerche,Ya'acov Ritov Pdf

This volume is a collection of papers presented at a conference held in Shoresh Holiday Resort near Jerusalem, Israel, in December 2000 organized by the Israeli Ministry of Science, Culture and Sport. The theme of the conference was "Foundation of Statistical Inference: Applications in the Medical and Social Sciences and in Industry and the Interface of Computer Sciences". The following is a quotation from the Program and Abstract booklet of the conference. "Over the past several decades, the field of statistics has seen tremendous growth and development in theory and methodology. At the same time, the advent of computers has facilitated the use of modern statistics in all branches of science, making statistics even more interdisciplinary than in the past; statistics, thus, has become strongly rooted in all empirical research in the medical, social, and engineering sciences. The abundance of computer programs and the variety of methods available to users brought to light the critical issues of choosing models and, given a data set, the methods most suitable for its analysis. Mathematical statisticians have devoted a great deal of effort to studying the appropriateness of models for various types of data, and defining the conditions under which a particular method work. " In 1985 an international conference with a similar title* was held in Is rael. It provided a platform for a formal debate between the two main schools of thought in Statistics, the Bayesian, and the Frequentists.

Author : R. Gilchrist
Publisher : Springer Science & Business Media
Page : 195 pages
File Size : 54,9 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781461257714

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GLIM 82: Proceedings of the International Conference on Generalised Linear Models by R. Gilchrist Pdf

This volume of Lecture Notes in Statistics consists of the published proceedings of the first international conference to be held on the topic of generalised linear models. This conference was held from 13 - 15 September 1982 at the Polytechnic of North London and marked an important stage in the development and expansion of the GLIM system. The range of the new system, tentatively named Prism, is here outlined by Bob Baker. Further sections of the volume are devoted to more detailed descriptions of the new facilities, including information on the two different numerical methods now available. Most of the data analyses in this volume are carried out using the GLIM system but this is, of course, not necessary. There are other ways of analysing generalised linear models and Peter Green here discusses the many attractive features of APL, including its ability to analyse generalised linear models. Later sections of the volume cover other invited and contributed papers on the theory and application of generalised linear models. Included amongst these is a paper by Murray Aitkin, proposing a unified approach to statistical modelling through direct likelihood inference, and a paper by Daryl Pregibon showing how GLIM can be programmed to carry out score tests. A paper by Joe Whittaker extends the recent discussion of the relationship between conditional independence and log-linear models and John Hinde considers the introduction of an independent random variable into a linear model to allow for unexplained variation in Poisson data.

Author : Kameo Matsushita
Publisher : North Holland
Page : 384 pages
File Size : 44,6 Mb
Release : 1980
Category : Mathematics
ISBN : UCAL:B4405453

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Recent Developments in Statistical Inference and Data Analysis by Kameo Matsushita Pdf

Enlarged mathematical representation for stochastic phenomena; Specification of statistical models by sufficiency;A modification of Brown's technique for proving inadmissibility; Estimating linear functional relationships; An empirical bayes approach to outliers: shifted mean case; Exploratory data analysis when data are matrices; Spatial patterns of territories; On the distribution of the likelihood ratio criterion for a covariance matrix; Some statistical methods of estimating the size of an animal population; Analysis of sentence structure by reordering processes; On the estimators for estimating variance of a normal distribution; Conditionality and maximum-likelihood estimation; Empirical bayes two-way decision in the case of discrete distributions; On an autoregressive model fitting and discrete spectra; The distributions of moving order statistics; Best invariant prediction region based on an adequate statistic; Estimation of the threshold parameter of the three parameter lognormal distributionA criterion for choosing the number of clusters in cluster analysis; On the development of SPMS as an effective tool for medical data analysis; Two approaches to nonparametric regression: splines & isotonic inference.

Author : Friedrich Pukelsheim
Publisher : SIAM
Page : 527 pages
File Size : 51,7 Mb
Release : 2006-04-01
Category : Mathematics
ISBN : 9780898716047

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Optimal Design of Experiments by Friedrich Pukelsheim Pdf

Optimal Design of Experiments offers a rare blend of linear algebra, convex analysis, and statistics. The optimal design for statistical experiments is first formulated as a concave matrix optimization problem. Using tools from convex analysis, the problem is solved generally for a wide class of optimality criteria such as D-, A-, or E-optimality. The book then offers a complementary approach that calls for the study of the symmetry properties of the design problem, exploiting such notions as matrix majorization and the Kiefer matrix ordering. The results are illustrated with optimal designs for polynomial fit models, Bayes designs, balanced incomplete block designs, exchangeable designs on the cube, rotatable designs on the sphere, and many other examples.

Author : Müjgan Tez,Dietrich von Rosen
Publisher : Springer
Page : 257 pages
File Size : 53,5 Mb
Release : 2018-02-01
Category : Mathematics
ISBN : 9783319732411

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Trends and Perspectives in Linear Statistical Inference by Müjgan Tez,Dietrich von Rosen Pdf

This volume features selected contributions on a variety of topics related to linear statistical inference. The peer-reviewed papers from the International Conference on Trends and Perspectives in Linear Statistical Inference (LinStat 2016) held in Istanbul, Turkey, 22-25 August 2016, cover topics in both theoretical and applied statistics, such as linear models, high-dimensional statistics, computational statistics, the design of experiments, and multivariate analysis. The book is intended for statisticians, Ph.D. students, and professionals who are interested in statistical inference.

Author : Anonim
Publisher : Unknown
Page : 1448 pages
File Size : 42,8 Mb
Release : 2003
Category : Mathematics
ISBN : UVA:X006180632

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Mathematical Reviews by Anonim Pdf

Author : Simo Puntanen,George P. H. Styan,Jarkko Isotalo
Publisher : Springer Science & Business Media
Page : 504 pages
File Size : 45,7 Mb
Release : 2011-08-24
Category : Mathematics
ISBN : 9783642104732

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Matrix Tricks for Linear Statistical Models by Simo Puntanen,George P. H. Styan,Jarkko Isotalo Pdf

In teaching linear statistical models to first-year graduate students or to final-year undergraduate students there is no way to proceed smoothly without matrices and related concepts of linear algebra; their use is really essential. Our experience is that making some particular matrix tricks very familiar to students can substantially increase their insight into linear statistical models (and also multivariate statistical analysis). In matrix algebra, there are handy, sometimes even very simple “tricks” which simplify and clarify the treatment of a problem—both for the student and for the professor. Of course, the concept of a trick is not uniquely defined—by a trick we simply mean here a useful important handy result. In this book we collect together our Top Twenty favourite matrix tricks for linear statistical models.

Author : George A. F. Seber
Publisher : John Wiley & Sons
Page : 592 pages
File Size : 43,9 Mb
Release : 2008-01-28
Category : Mathematics
ISBN : 9780470226780

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A Matrix Handbook for Statisticians by George A. F. Seber Pdf

A comprehensive, must-have handbook of matrix methods with a unique emphasis on statistical applications This timely book, A Matrix Handbook for Statisticians, provides a comprehensive, encyclopedic treatment of matrices as they relate to both statistical concepts and methodologies. Written by an experienced authority on matrices and statistical theory, this handbook is organized by topic rather than mathematical developments and includes numerous references to both the theory behind the methods and the applications of the methods. A uniform approach is applied to each chapter, which contains four parts: a definition followed by a list of results; a short list of references to related topics in the book; one or more references to proofs; and references to applications. The use of extensive cross-referencing to topics within the book and external referencing to proofs allows for definitions to be located easily as well as interrelationships among subject areas to be recognized. A Matrix Handbook for Statisticians addresses the need for matrix theory topics to be presented together in one book and features a collection of topics not found elsewhere under one cover. These topics include: Complex matrices A wide range of special matrices and their properties Special products and operators, such as the Kronecker product Partitioned and patterned matrices Matrix analysis and approximation Matrix optimization Majorization Random vectors and matrices Inequalities, such as probabilistic inequalities Additional topics, such as rank, eigenvalues, determinants, norms, generalized inverses, linear and quadratic equations, differentiation, and Jacobians, are also included. The book assumes a fundamental knowledge of vectors and matrices, maintains a reasonable level of abstraction when appropriate, and provides a comprehensive compendium of linear algebra results with use or potential use in statistics. A Matrix Handbook for Statisticians is an essential, one-of-a-kind book for graduate-level courses in advanced statistical studies including linear and nonlinear models, multivariate analysis, and statistical computing. It also serves as an excellent self-study guide for statistical researchers.

Author : Niall Adams,Martin Crowder,David J Hand,Dave Stephens
Publisher : World Scientific
Page : 260 pages
File Size : 51,6 Mb
Release : 2004-07-06
Category : Mathematics
ISBN : 9781783260690

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Methods and Models in Statistics by Niall Adams,Martin Crowder,David J Hand,Dave Stephens Pdf

John Nelder is one of today's leading statisticians, having made an impact on many parts of the discipline. This book contains reviews of some of those areas, written by top researchers. It is accessible to non-specialists, and is noteworthy for its breadth of coverage. Contents:John Nelder: From General Balance to Generalised Models (Both Linear and Hierarchical) (S Senn)Some Remarkes on Model Criticism (D R Cox)Likelihood Perspectives in the Consensus and Controversies of Statistical Modelling and Inference (Y Pawitan)Perspectives of ANOVA, REML and a General Linear Mixed Model (B R Cullis et al.)Algorithms, Data Structures and Languages — the Computational Ingredients for Innovative Analysis (R Payne)Non-Linear Regression Modelling and Inference (J C Wakefield)Selecting Amongst Large Classes of Models (B D Ripley)Principles of Designed Experiments in J A Nelder's Papers (R A Bailey)Likelihood-based Models Beyond GLMs (Y Lee)A Statistical Examination of the Hastings Rarities (J A Nelder) Readership: Students of statistics at masters or PhD level, as well as practising statisticians. Keywords:Statistics;John Nelder;Optimization;Likelihood;Statistical Modelling;Statistical Computing

Author : Rama Chellappa,Aswin C. Sankaranarayanan,Ashok Veeraraghavan,Pavan Turaga
Publisher : Now Publishers Inc
Page : 165 pages
File Size : 46,7 Mb
Release : 2010
Category : Computers
ISBN : 9781601983145

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Statistical Methods and Models for Video-based Tracking, Modeling, and Recognition by Rama Chellappa,Aswin C. Sankaranarayanan,Ashok Veeraraghavan,Pavan Turaga Pdf

Computer vision systems attempt to understand a scene and its components from mostly visual information. The geometry exhibited by the real world, the influence of material properties on scattering of incident light, and the process of imaging introduce constraints and properties that are key to solving some of these tasks. In the presence of noisy observations and other uncertainties, the algorithms make use of statistical methods for robust inference. In this paper, we highlight the role of geometric constraints in statistical estimation methods, and how the interplay of geometry and statistics leads to the choice and design of algorithms. In particular, we illustrate the role of imaging, illumination, and motion constraints in classical vision problems such as tracking, structure from motion, metrology, activity analysis and recognition, and appropriate statistical methods used in each of these problems.