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EBookClubs

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Book Statistical Inference for Models with Multivariate t Distributed Errors

Download or read book Statistical Inference for Models with Multivariate t Distributed Errors written by A. K. Md. Ehsanes Saleh and published by John Wiley & Sons. This book was released on 2014-10-01 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book summarizes the results of various models under normal theory with a brief review of the literature. Statistical Inference for Models with Multivariate t-Distributed Errors: Includes a wide array of applications for the analysis of multivariate observations Emphasizes the development of linear statistical models with applications to engineering, the physical sciences, and mathematics Contains an up-to-date bibliography featuring the latest trends and advances in the field to provide a collective source for research on the topic Addresses linear regression models with non-normal errors with practical real-world examples Uniquely addresses regression models in Student's t-distributed errors and t-models Supplemented with an Instructor's Solutions Manual, which is available via written request by the Publisher

Book Handbook Of Applied Econometrics And Statistical Inference

Download or read book Handbook Of Applied Econometrics And Statistical Inference written by Aman Ullah and published by CRC Press. This book was released on 2002-01-29 with total page 741 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summarizes developments and techniques in the field. It highlights areas such as sample surveys, nonparametic analysis, hypothesis testing, time series analysis, Bayesian inference, and distribution theory for applications in statistics, economics, medicine, biology, and engineering.

Book Bayesian Inference in Statistical Analysis

Download or read book Bayesian Inference in Statistical Analysis written by George E. P. Box and published by John Wiley & Sons. This book was released on 2011-01-25 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt: Its main objective is to examine the application and relevance of Bayes' theorem to problems that arise in scientific investigation in which inferences must be made regarding parameter values about which little is known a priori. Begins with a discussion of some important general aspects of the Bayesian approach such as the choice of prior distribution, particularly noninformative prior distribution, the problem of nuisance parameters and the role of sufficient statistics, followed by many standard problems concerned with the comparison of location and scale parameters. The main thrust is an investigation of questions with appropriate analysis of mathematical results which are illustrated with numerical examples, providing evidence of the value of the Bayesian approach.

Book Theory of Ridge Regression Estimation with Applications

Download or read book Theory of Ridge Regression Estimation with Applications written by A. K. Md. Ehsanes Saleh and published by John Wiley & Sons. This book was released on 2019-02-12 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to the systematic analytical results for ridge, LASSO, preliminary test, and Stein-type estimators with applications Theory of Ridge Regression Estimation with Applications offers a comprehensive guide to the theory and methods of estimation. Ridge regression and LASSO are at the center of all penalty estimators in a range of standard models that are used in many applied statistical analyses. Written by noted experts in the field, the book contains a thorough introduction to penalty and shrinkage estimation and explores the role that ridge, LASSO, and logistic regression play in the computer intensive area of neural network and big data analysis. Designed to be accessible, the book presents detailed coverage of the basic terminology related to various models such as the location and simple linear models, normal and rank theory-based ridge, LASSO, preliminary test and Stein-type estimators. The authors also include problem sets to enhance learning. This book is a volume in the Wiley Series in Probability and Statistics series that provides essential and invaluable reading for all statisticians. This important resource: Offers theoretical coverage and computer-intensive applications of the procedures presented Contains solutions and alternate methods for prediction accuracy and selecting model procedures Presents the first book to focus on ridge regression and unifies past research with current methodology Uses R throughout the text and includes a companion website containing convenient data sets Written for graduate students, practitioners, and researchers in various fields of science, Theory of Ridge Regression Estimation with Applications is an authoritative guide to the theory and methodology of statistical estimation.

Book Multivariate T Distributions and Their Applications

Download or read book Multivariate T Distributions and Their Applications written by Samuel Kotz and published by Cambridge University Press. This book was released on 2004-02-16 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Almost all the results available in the literature on multivariate t-distributions published in the last 50 years are now collected together in this comprehensive reference. Because these distributions are becoming more prominent in many applications, this book is a must for any serious researcher or consultant working in multivariate analysis and statistical distributions. Much of this material has never before appeared in book form. The first part of the book emphasizes theoretical results of a probabilistic nature. In the second part of the book, these are supplemented by a variety of statistical aspects. Various generalizations and applications are dealt with in the final chapters. The material on estimation and regression models is of special value for practitioners in statistics and economics. A comprehensive bibliography of over 350 references is included.

Book Financial Statistics and Data Analytics

Download or read book Financial Statistics and Data Analytics written by Shuangzhe Li and published by MDPI. This book was released on 2021-03-02 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern financial management is largely about risk management, which is increasingly data-driven. The problem is how to extract information from the data overload. It is here that advanced statistical and machine learning techniques can help. Accordingly, finance, statistics, and data analytics go hand in hand. The purpose of this book is to bring the state-of-art research in these three areas to the fore and especially research that juxtaposes these three.

Book Mobile Agent Based Anomaly Detection and Verification System for Smart Home Sensor Networks

Download or read book Mobile Agent Based Anomaly Detection and Verification System for Smart Home Sensor Networks written by Muhammad Usman and published by Springer. This book was released on 2018-01-31 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest developments regarding a detailed mobile agent-enabled anomaly detection and verification system for resource constrained sensor networks; a number of algorithms on multi-aspect anomaly detection in sensor networks; several algorithms on mobile agent transmission optimization in resource constrained sensor networks; an algorithm on mobile agent-enabled in situ verification of anomalous sensor nodes; a detailed Petri Net-based formal modeling and analysis of the proposed system, and an algorithm on fuzzy logic-based cross-layer anomaly detection and mobile agent transmission optimization. As such, it offers a comprehensive text for interested readers from academia and industry alike.

Book Rank Based Methods for Shrinkage and Selection

Download or read book Rank Based Methods for Shrinkage and Selection written by A. K. Md. Ehsanes Saleh and published by John Wiley & Sons. This book was released on 2022-03-22 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rank-Based Methods for Shrinkage and Selection A practical and hands-on guide to the theory and methodology of statistical estimation based on rank Robust statistics is an important field in contemporary mathematics and applied statistical methods. Rank-Based Methods for Shrinkage and Selection: With Application to Machine Learning describes techniques to produce higher quality data analysis in shrinkage and subset selection to obtain parsimonious models with outlier-free prediction. This book is intended for statisticians, economists, biostatisticians, data scientists and graduate students. Rank-Based Methods for Shrinkage and Selection elaborates on rank-based theory and application in machine learning to robustify the least squares methodology. It also includes: Development of rank theory and application of shrinkage and selection Methodology for robust data science using penalized rank estimators Theory and methods of penalized rank dispersion for ridge, LASSO and Enet Topics include Liu regression, high-dimension, and AR(p) Novel rank-based logistic regression and neural networks Problem sets include R code to demonstrate its use in machine learning

Book Nonstationary Systems  Theory and Applications

Download or read book Nonstationary Systems Theory and Applications written by Fakher Chaari and published by Springer Nature. This book was released on 2021-07-21 with total page 439 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers an overview of current and recent methods for the analysis of the nonstationary processes, focusing on cyclostationary systems that are ubiquitous in various application fields. Based on the 13th Workshop on Nonstationary Systems and Their Applications, held on February 3-5, 2020, in Grodek nad Dunajcem, Poland, the book merges theoretical contributions describing new statistical and intelligent methods for analyzing nonstationary processes, and applied works showing how the proposed methods can be implemented in practice and do perform in real-world case studies. A significant part of the book is dedicated to nonstationary systems applications, with a special emphasis on those in condition monitoring.

Book Simultaneous Statistical Inference

Download or read book Simultaneous Statistical Inference written by Thorsten Dickhaus and published by Springer Science & Business Media. This book was released on 2014-01-23 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph will provide an in-depth mathematical treatment of modern multiple test procedures controlling the false discovery rate (FDR) and related error measures, particularly addressing applications to fields such as genetics, proteomics, neuroscience and general biology. The book will also include a detailed description how to implement these methods in practice. Moreover new developments focusing on non-standard assumptions are also included, especially multiple tests for discrete data. The book primarily addresses researchers and practitioners but will also be beneficial for graduate students.

Book Simultaneous Statistical Inference

Download or read book Simultaneous Statistical Inference written by Rupert G. Miller and published by Springer. This book was released on 1981-03-18 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: Normal univariate techniques; regression techniques; nonparametric techniques; multivariate techniques; miscellaneous techniques; strong law for the expected error rate; tables; developments in multiple comparisons 1966-1976; addendum new table of the studentized maximum modulus.

Book Multivariate Statistical Inference

Download or read book Multivariate Statistical Inference written by Narayan C. Giri and published by . This book was released on 1977 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Proceedings of the International Conference on Linear Statistical Inference LINSTAT    93

Download or read book Proceedings of the International Conference on Linear Statistical Inference LINSTAT 93 written by Tadeusz Calinski and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book James Stein Rule Estimators in Linear Regression Models with Errors Having Multivariate Student t Distribution

Download or read book James Stein Rule Estimators in Linear Regression Models with Errors Having Multivariate Student t Distribution written by Radhey S. Singh and published by Guelph, Ont. : Department of Mathematics and Statistics, University of Guelph. This book was released on 1989 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Generalized Inference in Repeated Measures

Download or read book Generalized Inference in Repeated Measures written by Samaradasa Weerahandi and published by John Wiley & Sons. This book was released on 2004-08-24 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete guide to powerful and practical statistical modeling using MANOVA Numerous statistical applications are time dependent. Virtually all biomedical, pharmaceutical, and industrial experiments demand repeated measurements over time. The same holds true for market research and analysis. Yet conventional methods, such as the Repeated Measures Analysis of Variance (Rm ANOVA), do not always yield exact solutions, obliging practitioners to settle for asymptotic results and approximate solutions. Generalized inference in Multivariate Analysis of Variance (MANOVA), mixed models, and growth curves offer exact methods of data analysis under milder conditions without deviating from the conventional philosophy of statistical inference. Generalized Inference in Repeated Measures is a concise, self-contained guide to the use of these innovative solutions, presenting them as extensions of–rather than alternatives to–classical methods of statistical evaluation. Requiring minimal prior knowledge of statistical concepts in the evaluation of linear models, the book provides exact parametric methods for each application considered, with solutions presented in terms of generalized p-values. Coverage includes: New concepts in statistical inference, with special focus on generalized p-values and generalized confidence intervals One-way and two-way ANOVA, in cases of equal and unequal variances Basic and higher-way mixed models, including testing and estimation of fixed effects and variance components Multivariate populations, including basic inference, comparison, and analysis of variance Basic, widely used repeated measures models including crossover designs and growth curves With a comprehensive set of formulas, illustrative examples, and exercises in each chapter, Generalized Inference in Repeated Measures is ideal as both a comprehensive reference for research professionals and a text for students.