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Author: Shayle R. Searle
Publisher: John Wiley & Sons
ISBN: 0470040041
Category : Mathematics
Languages : en
Pages : 570
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Book Description
WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "[This book] provides an excellent discussion of the methodology and interpretation of linear models analysis of unbalanced data (data having unequal numbers of observations in the subclasses), generally without matrices?the author does an excellent job of emphasizing the more practical nature of the book. Highly recommended for graduate and undergraduate libraries." â?"Choice "This is a very comprehensive text, aimed at both students studying linear-model theory and practicing statisticians who require an understanding of the model-fitting procedures incorporated in statistical packages?This book should be considered as a text for college courses as it provides a clearly presented and thorough treatment of linear models. It will also be useful to any practicing statistician who has to analyze unbalanced data, perhaps arising from surveys, and wishes to understand the output from model-fitting procedures and the discrepancies in analysis from one recognized package to another." â?"Biometrics This newly available and affordably priced paperback version of Linear Models for Unbalanced Data offers a presentation of the fundamentals of linear statistical models unique in its total devotion to unbalanced data and its emphasis on the up-to-date cell means model approach to linear models for unbalanced data. Topic coverage includes cell means models, 1-way classification, nested classifications, 2-way classification with some-cells-empty data, models with covariables, matrix algebra and quadratic forms, linear model theory, and much more.
Author: Shayle R. Searle
Publisher: John Wiley & Sons
ISBN: 0470040041
Category : Mathematics
Languages : en
Pages : 570
Get Book Here
Book Description
WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "[This book] provides an excellent discussion of the methodology and interpretation of linear models analysis of unbalanced data (data having unequal numbers of observations in the subclasses), generally without matrices?the author does an excellent job of emphasizing the more practical nature of the book. Highly recommended for graduate and undergraduate libraries." â?"Choice "This is a very comprehensive text, aimed at both students studying linear-model theory and practicing statisticians who require an understanding of the model-fitting procedures incorporated in statistical packages?This book should be considered as a text for college courses as it provides a clearly presented and thorough treatment of linear models. It will also be useful to any practicing statistician who has to analyze unbalanced data, perhaps arising from surveys, and wishes to understand the output from model-fitting procedures and the discrepancies in analysis from one recognized package to another." â?"Biometrics This newly available and affordably priced paperback version of Linear Models for Unbalanced Data offers a presentation of the fundamentals of linear statistical models unique in its total devotion to unbalanced data and its emphasis on the up-to-date cell means model approach to linear models for unbalanced data. Topic coverage includes cell means models, 1-way classification, nested classifications, 2-way classification with some-cells-empty data, models with covariables, matrix algebra and quadratic forms, linear model theory, and much more.
Author: Beong-Soo So
Publisher:
ISBN:
Category :
Languages : en
Pages : 146
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Book Description
Author: Regina Y. Liu
Publisher: Springer
ISBN: 3319390651
Category : Mathematics
Languages : en
Pages : 284
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Book Description
The contributors to this volume include many of the distinguished researchers in this area. Many of these scholars have collaborated with Joseph McKean to develop underlying theory for these methods, obtain small sample corrections, and develop efficient algorithms for their computation. The papers cover the scope of the area, including robust nonparametric rank-based procedures through Bayesian and big data rank-based analyses. Areas of application include biostatistics and spatial areas. Over the last 30 years, robust rank-based and nonparametric methods have developed considerably. These procedures generalize traditional Wilcoxon-type methods for one- and two-sample location problems. Research into these procedures has culminated in complete analyses for many of the models used in practice including linear, generalized linear, mixed, and nonlinear models. Settings are both multivariate and univariate. With the development of R packages in these areas, computation of these procedures is easily shared with readers and implemented. This book is developed from the International Conference on Robust Rank-Based and Nonparametric Methods, held at Western Michigan University in April 2015.
Author: Dimitrios Asteriou
Publisher: Bloomsbury Publishing
ISBN: 1350306142
Category : Business & Economics
Languages : en
Pages : 1242
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Book Description
This trusted textbook returns in its 4th edition with even more exercises to help consolidate understanding - and a companion website featuring additional materials, including a solutions manual for instructors. Offering a unique blend of theory and practical application, it provides ideal preparation for doing applied econometric work as it takes students from a basic level up to an advanced understanding in an intuitive, step-by-step fashion. Clear presentation of economic tests and methods of estimation is paired with practical guidance on using several types of software packages. Using real world data throughout, the authors place emphasis upon the interpretation of results, and the conclusions to be drawn from them in econometric work. This book will be essential reading for economics undergraduate and master's students taking a course in applied econometrics. Its practical nature makes it ideal for modules requiring a research project. New to this Edition: - Additional practical exercises throughout to help consolidate understanding - A freshly-updated companion website featuring a new solutions manual for instructors
Author:
Publisher:
ISBN:
Category : Weights and measures
Languages : en
Pages : 574
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Book Description
Author:
Publisher:
ISBN:
Category : Statistics
Languages : en
Pages : 882
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Book Description
Author:
Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 924
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Book Description
Author: M. Hashem Pesaran
Publisher: Oxford University Press
ISBN: 0198736916
Category : Business & Economics
Languages : en
Pages : 1095
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Book Description
This book is concerned with recent developments in time series and panel data techniques for the analysis of macroeconomic and financial data. It provides a rigorous, nevertheless user-friendly, account of the time series techniques dealing with univariate and multivariate time series models, as well as panel data models. It is distinct from other time series texts in the sense that it also covers panel data models and attempts at a more coherent integration of time series, multivariate analysis, and panel data models. It builds on the author's extensive research in the areas of time series and panel data analysis and covers a wide variety of topics in one volume. Different parts of the book can be used as teaching material for a variety of courses in econometrics. It can also be used as reference manual. It begins with an overview of basic econometric and statistical techniques, and provides an account of stochastic processes, univariate and multivariate time series, tests for unit roots, cointegration, impulse response analysis, autoregressive conditional heteroskedasticity models, simultaneous equation models, vector autoregressions, causality, forecasting, multivariate volatility models, panel data models, aggregation and global vector autoregressive models (GVAR). The techniques are illustrated using Microfit 5 (Pesaran and Pesaran, 2009, OUP) with applications to real output, inflation, interest rates, exchange rates, and stock prices.
Author: Yan Liu
Publisher: Springer Nature
ISBN: 9819908035
Category : Mathematics
Languages : en
Pages : 591
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Book Description
This book compiles theoretical developments on statistical inference for time series and related models in honor of Masanobu Taniguchi's 70th birthday. It covers models such as long-range dependence models, nonlinear conditionally heteroscedastic time series, locally stationary processes, integer-valued time series, Lévy Processes, complex-valued time series, categorical time series, exclusive topic models, and copula models. Many cutting-edge methods such as empirical likelihood methods, quantile regression, portmanteau tests, rank-based inference, change-point detection, testing for the goodness-of-fit, higher-order asymptotic expansion, minimum contrast estimation, optimal transportation, and topological methods are proposed, considered, or applied to complex data based on the statistical inference for stochastic processes. The performances of these methods are illustrated by a variety of data analyses. This collection of original papers provides the reader with comprehensive and state-of-the-art theoretical works on time series and related models. It contains deep and profound treatments of the asymptotic theory of statistical inference. In addition, many specialized methodologies based on the asymptotic theory are presented in a simple way for a wide variety of statistical models. This Festschrift finds its core audiences in statistics, signal processing, and econometrics.
Author: American Statistical Association
Publisher:
ISBN:
Category : Electronic journals
Languages : en
Pages : 888
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Book Description
