Download or read book Estimation of a Linear Regression Model when the Variance is a Linear Function of Unknown Parameters written by Huei Chu Tsai and published by . This book was released on 1976 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Estimation of a Nonlinear Regression Model when the Variance is a Linear Function of Unknown Parameters written by Huei-chu Tsai and published by . This book was released on 1976 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Parameter Estimation and Hypothesis Testing in Linear Models written by Karl-Rudolf Koch and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: A treatment of estimating unknown parameters, testing hypotheses and estimating confidence intervals in linear models. Readers will find here presentations of the Gauss-Markoff model, the analysis of variance, the multivariate model, the model with unknown variance and covariance components and the regression model as well as the mixed model for estimating random parameters. A chapter on the robust estimation of parameters and several examples have been added to this second edition. The necessary theorems of vector and matrix algebra and the probability distributions of test statistics are derived so as to make this book self-contained. Geodesy students as well as those in the natural sciences and engineering will find the emphasis on the geodetic application of statistical models extremely useful.

Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1989 with total page 984 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Advanced Linear Models written by Shein-Chung Chow and published by Routledge. This book was released on 2018-05-04 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work details the statistical inference of linear models including parameter estimation, hypothesis testing, confidence intervals, and prediction. The authors discuss the application of statistical theories and methodologies to various linear models such as the linear regression model, the analysis of variance model, the analysis of covariance model, and the variance components model.

Download or read book Understanding Regression Analysis written by Michael Patrick Allen and published by Springer Science & Business Media. This book was released on 2007-11-23 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: By assuming it is possible to understand regression analysis without fully comprehending all its underlying proofs and theories, this introduction to the widely used statistical technique is accessible to readers who may have only a rudimentary knowledge of mathematics. Chapters discuss: -descriptive statistics using vector notation and the components of a simple regression model; -the logic of sampling distributions and simple hypothesis testing; -the basic operations of matrix algebra and the properties of the multiple regression model; -testing compound hypotheses and the application of the regression model to the analyses of variance and covariance, and -structural equation models and influence statistics.

Download or read book Regression written by N. H. Bingham and published by Springer Science & Business Media. This book was released on 2010-09-17 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: Regression is the branch of Statistics in which a dependent variable of interest is modelled as a linear combination of one or more predictor variables, together with a random error. The subject is inherently two- or higher- dimensional, thus an understanding of Statistics in one dimension is essential. Regression: Linear Models in Statistics fills the gap between introductory statistical theory and more specialist sources of information. In doing so, it provides the reader with a number of worked examples, and exercises with full solutions. The book begins with simple linear regression (one predictor variable), and analysis of variance (ANOVA), and then further explores the area through inclusion of topics such as multiple linear regression (several predictor variables) and analysis of covariance (ANCOVA). The book concludes with special topics such as non-parametric regression and mixed models, time series, spatial processes and design of experiments. Aimed at 2nd and 3rd year undergraduates studying Statistics, Regression: Linear Models in Statistics requires a basic knowledge of (one-dimensional) Statistics, as well as Probability and standard Linear Algebra. Possible companions include John Haigh’s Probability Models, and T. S. Blyth & E.F. Robertsons’ Basic Linear Algebra and Further Linear Algebra.

Download or read book Applied Statistics and Probability for Engineers written by Douglas C. Montgomery and published by John Wiley & Sons. This book was released on 2020-07-08 with total page 722 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Statistics and Probability for Engineers provides a practical approach to probability and statistical methods. Students learn how the material will be relevant in their careers by including a rich collection of examples and problem sets that reflect realistic applications and situations. This product focuses on real engineering applications and real engineering solutions while including material on the bootstrap, increased emphasis on the use of p-value, coverage of equivalence testing, and combining p-values. The base content, examples, exercises and answers presented in this product have been meticulously checked for accuracy. The Enhanced E-Text is also available bundled with an abridged print companion and can be ordered by contacting customer service here: ISBN: 9781119456261 Price: $97.95 Canadian Price: $111.50

Download or read book Linear Regression Analysis Theory And Computing written by Xin Yan and published by World Scientific. This book was released on 2009-06-05 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents in detail the fundamental theories of linear regression analysis and diagnosis, as well as the relevant statistical computing techniques so that readers are able to actually model the data using the methods and techniques described in the book. It covers the fundamental theories in linear regression analysis and is extremely useful for future research in this area. The examples of regression analysis using the Statistical Application System (SAS) are also included. This book is suitable for graduate students who are either majoring in statistics/biostatistics or using linear regression analysis substantially in their subject fields.

Download or read book Regression Analysis written by Fouad Sabry and published by One Billion Knowledgeable. This book was released on 2024-02-04 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is Regression Analysis In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships between a dependent variable and one or more independent variables. The most common form of regression analysis is linear regression, in which one finds the line that most closely fits the data according to a specific mathematical criterion. For example, the method of ordinary least squares computes the unique line that minimizes the sum of squared differences between the true data and that line. For specific mathematical reasons, this allows the researcher to estimate the conditional expectation of the dependent variable when the independent variables take on a given set of values. Less common forms of regression use slightly different procedures to estimate alternative location parameters or estimate the conditional expectation across a broader collection of non-linear models. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Regression analysis Chapter 2: Least squares Chapter 3: Gauss-Markov theorem Chapter 4: Nonlinear regression Chapter 5: Coefficient of determination Chapter 6: Instrumental variables estimation Chapter 7: Omitted-variable bias Chapter 8: Ordinary least squares Chapter 9: Residual sum of squares Chapter 10: Simple linear regression Chapter 11: Generalized least squares Chapter 12: Heteroskedasticity-consistent standard errors Chapter 13: Variance inflation factor Chapter 14: Non-linear least squares Chapter 15: Principal component regression Chapter 16: Lack-of-fit sum of squares Chapter 17: Leverage (statistics) Chapter 18: Polynomial regression Chapter 19: Errors-in-variables models Chapter 20: Linear least squares Chapter 21: Linear regression (II) Answering the public top questions about regression analysis. (III) Real world examples for the usage of regression analysis in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Regression Analysis.

Download or read book Probability Random Signals and Statistics written by X. Rong Li and published by CRC Press. This book was released on 2017-12-14 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: With this innovative text, the study-and teaching- of probability and random signals becomes simpler, more streamlined, and more effective. Its unique "textgraph" format makes it both student-friendly and instructor-friendly. Pages with a larger typeface form a concise text for basic topics and make ideal transparencies; pages with smaller type provide more detailed explanations and more advanced material.

Download or read book Business Statistics written by J. K. Sharma and published by Pearson Education India. This book was released on 2012 with total page 752 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this edition, efforts have been made to assist readers in converting data into useful information that can be used by decision-makers in making more thoughtful, information-based decisions.

Download or read book Statistical Inference written by George Casella and published by CRC Press. This book was released on 2024-05-23 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: This classic textbook builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and natural extensions, and consequences, of previous concepts. It covers all topics from a standard inference course including: distributions, random variables, data reduction, point estimation, hypothesis testing, and interval estimation. Features The classic graduate-level textbook on statistical inference Develops elements of statistical theory from first principles of probability Written in a lucid style accessible to anyone with some background in calculus Covers all key topics of a standard course in inference Hundreds of examples throughout to aid understanding Each chapter includes an extensive set of graduated exercises Statistical Inference, Second Edition is primarily aimed at graduate students of statistics, but can be used by advanced undergraduate students majoring in statistics who have a solid mathematics background. It also stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures, while less focused on formal optimality considerations. This is a reprint of the second edition originally published by Cengage Learning, Inc. in 2001.

Download or read book The Oxford Dictionary of Statistical Terms written by Yadolah Dodge and published by Oxford University Press, USA. This book was released on 2003 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the new-in-paperback edition of The Oxford Dictionary of Statistical Terms, the much-awaited sixth edition of the acclaimed standard reference work in statistics, published on behalf of the International Statistical Institute. The first edition, known as the Dictionary of Statistical Terms, was edited in 1957 by the late Sir Maurice Kendall and the late Dr W.R. Buckland. As one of the first dictionaries of statistics it set high standards for the subject, and became a well-respected reference. This edition has been carefully updated and extended to include the most recent terminology and techniques in statistics. Significant revision and expansion from an international editorial board of senior statisticians has resulted in a comprehenisive reference text which includes 30% more material than previous editions. Ideal for all who use statistics in the workplace and in research including all scientists and social scientists, especially in law, politics, finance, business, and history, it is an indispensable reference.

Download or read book Probability and Conditional Expectation written by Rolf Steyer and published by John Wiley & Sons. This book was released on 2017-02-22 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probability and Conditional Expectations bridges the gap between books on probability theory and statistics by providing the probabilistic concepts estimated and tested in analysis of variance, regression analysis, factor analysis, structural equation modeling, hierarchical linear models and analysis of qualitative data. The authors emphasize the theory of conditional expectations that is also fundamental to conditional independence and conditional distributions. Probability and Conditional Expectations Presents a rigorous and detailed mathematical treatment of probability theory focusing on concepts that are fundamental to understand what we are estimating in applied statistics. Explores the basics of random variables along with extensive coverage of measurable functions and integration. Extensively treats conditional expectations also with respect to a conditional probability measure and the concept of conditional effect functions, which are crucial in the analysis of causal effects. Is illustrated throughout with simple examples, numerous exercises and detailed solutions. Provides website links to further resources including videos of courses delivered by the authors as well as R code exercises to help illustrate the theory presented throughout the book.

Download or read book Estimation in Simple Linear Regression with a Nested Error written by Bilgehan Guven and published by . This book was released on 1992 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Systems Biology written by Edda Klipp and published by John Wiley & Sons. This book was released on 2011-09-19 with total page 593 pages. Available in PDF, EPUB and Kindle. Book excerpt: This advanced textbook is tailored to the needs of introductory course in Systems Biology. It has a compagnion website (WWW.WILEY-VCH.DE/HOME/SYSTEMSBIOLOGY) with solutions to questions in the book and several additional extensive working models. The book is related to the very successful previous title 'Systems Biology in Practice' and has incorporated the feedback and suggestions from many lecturers worldwide. The book addresses biologists as well as engineers and computer scientists. The interdisciplinary team of acclaimed authors worked closely together to ensure a comprehensive coverage with no overlaps in a homogenous and compelling style.