New York: Cengage Learning, 2005. — 450 p. Looking for an easy-to-understand text to guide you through the tough topic of regression modeling? INTRODUCTION TO REGRESSION MODELING (WITH CD-ROM) offers a blend of theory and regression applications and will give you the practice you need to tackle this subject through exercises, case studies. and projects that have you identify a...
Wiley, 2021. — 499 p. — ISBN 9781119715177. A thorough presentation of Quantile Regression designed to help readers obtain richer information from data analyses The conditional least-square or mean-regression (MR) analysis is the quantitative research method used to model and analyze the relationships between a dependent variable and one or more independent variables, where...
Wiley, 2021. — 499 p. — ISBN 9781119715177. A thorough presentation of Quantile Regression designed to help readers obtain richer information from data analyses The conditional least-square or mean-regression (MR) analysis is the quantitative research method used to model and analyze the relationships between a dependent variable and one or more independent variables, where...
AI Publishing, 2020. — 128 p. Linear and Logistic Regressions with Python for Beginners with Hands-On ProjectsAre you looking for a hands-on approach to learn Regression fast? Or perhaps you have just completed a Data Science or Python course and are looking for data science models?Do you need to start learning Logistic and Linear Regression from Scratch?This book is for you....
Sage Publications, 1991. — 220 p. This successful book, now available in paperback, provides academics and researchers with a clear set of prescriptions for estimating, testing and probing interactions in regression models. Including the latest research in the area, such as Fuller′s work on the corrected/constrained estimator, the book is appropriate for anyone who uses...
Philadelphia: Sage Publications, 1984. — 95 p. Specification of Nonlinear Probability Models Estimation of Probit and Logit Models for Dichotomous Dependent Variables Minimum Chi-Square Estimation and Polytomous Models Summary and Extensions Notes
New York: Springer, 1997. — 226 p. 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...
Philadelphia: SAGE Publications, 1998. — 242 p. Multiple regression is at the heart of social science data analysis, because it deals with explanations and correlations. This book is a complete introduction to this statistical method. This textbook is designed for the first social statistics course a student takes and, unlike other titles aimed at a higher level, has been...
N.-Y.: Springer, 2010. — 494 p. This text provides, in a non-technical language, a unified treatment of regression models for different outcome types, such as linear regression, logistic regression, and Cox regression. This is done by focusing on the many common aspects of these models, in particular the linear predictor, which combines the effects of all explanatory variables...
Routledge, 2019. — 363 p. — ISBN: 978-1-138-54140-5. With the rise of "big data," there is an increasing demand to learn the skills needed to undertake sound quantitative analysis without requiring students to spend too much time on high-level math and proofs. This book provides an efficient alternative approach, with more time devoted to the practical aspects of regression...
2nd Edition. — Routledge, 2023. — 392 p. — ISBN 978-1-032-25783-9. This thoroughly practical and engaging textbook is designed to equip students with the skills needed to undertake sound regression analysis without requiring high-level math. Regression Analysis covers the concepts needed to design optimal regression models and to properly interpret regressions. It details the...
Muthén & Muthén, 2016. — 266 p. The inspiration to write this book came from many years of teaching about Mplus and answering questions on Mplus Discussion and Mplus support. It became clear that once people leave school, it is difficult to keep up with the newest methodology. The purpose of this book is to provide researchers with information that is not readily available to...
Springer, 2000. — 328 p.
This book is about using graphs to understand the relationship between a regression model and the data to which it is fitted. Because of the new way in which models are fitted, for example by least squares, we can lose information about the effect of individual observations on inferences about the form and parameters of the model. The methods developed...
Oxford University Press, 1987. — 300 p. This handbook provides a detailed, down-to-earth introduction to regression diagnostic analysis, a technique of growing importance for work in applied statistics. Heavily illustrated, with numerous examples to illuminate the discussion, this timely volume outlines methods for regression models, stressing detection of outliers and...
Wiley, 1988. - 365 с. Бейтс Д.М., Уоттс Д. Нелинейный регрессионный анализ и его приложения. Представлены теоретические, практические и расчетные аспекты нелинейной регрессии. В книге содержится материал по линейной регрессии. Presents the theoretical, practical, and computational aspects of nonlinear regression. This book provides material on linear regression, including a...
Nova Science Publishers, Inc., 2017. — 193 p. — (Mathematics Research Developments). — ISBN: 153611992X. Chapter One addresses the importance of weighted linear regression in fitting straight lines. In Chapter Two, the authors cover the homocedastic condition, i.e., variance of y's independent of x, errors of y's accumulative, the heterocedastic case, i.e., variance or standard...
Thousands Oaks: Sage Publications, 2004. — 281 p. Regression is often applied to questions for which it is ill equipped to answer. As a formal matter, conventional regression analysis does nothing more than produce from a data set a collection of conditional means and conditional variances. The problem, though, is that researchers typically want more: they want tests,...
Thousands Oaks: Sage Publications, 2004. — 281 p. Regression is often applied to questions for which it is ill equipped to answer. As a formal matter, conventional regression analysis does nothing more than produce from a data set a collection of conditional means and conditional variances. The problem, though, is that researchers typically want more: they want tests,...
Cambridge University Press, 2021. — 350 p. — ISBN: 9781108492263. The Cobb-Douglas regression, a statistical technique developed to estimate what economists called a 'production function', was introduced in the late 1920s. For several years, only economist Paul Douglas and a few collaborators used the technique, while vigorously defending it against numerous critics. By the...
Springer-Verlag London Limited 2010. - 293 pages. Format PDF 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:...
Wiley – 1993, 240 pages ISBN: 0471568813, 9780471568810 An introduction to a variety of regression methods including linear, least-squares, least-absolute- deviations, robust M, nonparameter rank-based, Bayesian and ridge regressions. Each chapter contains sections on estimating the regression line for simple regression data, testing the slope of the regression line, estimating...
Nova Science Publishers, 2013. — 171 p. This text addresses two interrelated problems in economics non-nested hypothesis testing in econometrics, and regression models with stochastic/random regressors. The primary motivation for this book stems from the nature of econometric models. Preface Acknowledgment Introduction Recent Development in Non-nested Regression Asymptotic...
Springer, 2020. — 70 p. — (SpringerBriefs in Statistics). — ISBN: 978-3-030-57934-0. This book provides an updated account of the regression techniques employed in comparing analytical methods and to test the biases of one method relative to others – a problem commonly found in fields like analytical chemistry, biology, engineering, and medicine. Methods comparison involves a...
Springer, 2020. — 64 p. — (SpringerBriefs in Statistics - ABE). — ISBN: 978-3-030-57934-0, 978-3-030-57935-7. This book provides an updated account of the regression techniques employed in comparing analytical methods and to test the biases of one method relative to others – a problem commonly found in fields like analytical chemistry, biology, engineering, and medicine....
CRC Press, 2022. — 193 p. Regression Analysis in R: A Comprehensive View for the Social Sciences covers the basic applications of multiple linear regression all the way through to more complex regression applications and extensions. Written for graduate level students of social science disciplines this book walks readers through bivariate correlation giving them a solid...
Oxford: Business Expert Press, 2015. — 220 p. Regression Analysis: Unified Concepts, Practical Applications, Computer Implementation is a concise and innovative book that gives a complete presentation of applied regression analysis in approximately one-half the space of competing books. With only the modest prerequisite of a basic (non-calculus) statistics course this text is...
Boca Raton: CRC Press, 2018. — 252 p. For a solid foundation of important statistical methods, the concise, single-source text unites linear regression with analysis of experiments and provides students with the practical understanding needed to apply theory in real data analysis problems. Stressing principles while keeping computational and theoretical details at a manageable...
Independently published, 2022. — 132 p. What's Special about this Book: The ideal reader for this book will be quantitatively literate and has a basic understanding of statistical concepts and R programming. The student should have a basic understanding of statistical inference such as contained in "Statistical inference for Data Science". The book gives a rigorous treatment of...
Cambridge, Cambridge University Press, 1998. - 434p.
Монография посвящена построению регрессионных моделей при условии, что зависимая переменная является целочисленной величиной. Рассматриваются пуассоновские, обратно биномиальные и другие модели порождения данных, обобщения их, включая случай гетероскедастичности, цензурованных и усечённых наблюдений, различные методы...
The Guilford Press, 1999. — 224 p. Regression toward the mean is a complex statistical principle that plays a crucial role in any research involving the measurement of change. This primer is designed to help researchers more fully understand this phenomenon and avoid common errors in interpretation. The book presents new methods of graphing regression toward the mean,...
5th ed. — Wiley, 2012. — 424 p. — ISBN: 0470905840, 9780470905845. Regression Analysis by Example, FifthEdition has been expanded and thoroughly updated to reflectrecent advances in the field. The emphasis continues to be onexploratory data analysis rather than statistical theory. The bookoffers in-depth treatment of regression diagnostics,transformation, multicollinearity,...
Wiley, 2006. — 366 p. — ISBN 978047174696-6. The essentials of regression analysis through practical applications Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgement....
N.-Y.: Wiley, 1988. - 323p.
Treats linear regression diagnostics as a tool for application of linear regression models to real-life data. Presentation makes extensive use of examples to illustrate theory. Assesses the effect of measurement errors on the estimated coefficients, which is not accounted for in a standard least squares estimate but is important where regression...
Wiley, 2013. — 236 p. — ISBN 0470887168, 9780470887165 A Comprehensive Account for Data Analysts of the Methods and Applications of Regression Analysis. Written by two established experts in the field, the purpose of the Handbook of Regression Analysis is to provide a practical, one-stop reference on regression analysis. The focus is on the tools that both practitioners and...
2nd ed. — Hoboken (NJ): John Wiley & Sons, 2020. — 363 p. — (Wiley Series in Probability and Statistics). — ISBN 1119392373. Handbook and reference guide for students and practitioners of statistical regression-based analyses in R. Handbook of Regression Analysis with Applications in R, Second Edition is a comprehensive and up-to-date guide to conducting complex regressions in...
2nd Edition. — Boca Raton: CRC Press, 2016. — 632 p. — e-ISBN: 978-1-4987-7405-5 Probability Random variables and expectations Continuous distributions The binomial distribution The multinomial distribution One Sample Example and introduction Parametric inference about mu Prediction intervals Model testing Checking normality Transformations Inference about sigma2 General...
Second Edition. — N.-Y.: Springer, 1997. — 523 p. — ISBN: 0387982477, 978-0387982472.
The primary focus here is on log-linear models for contingency tables, but in this second edition, greater emphasis has been placed on logistic regression. The book explores topics such as logistic discrimination and generalised linear models, and builds upon the relationships between these...
2nd edition. — New York: Springer, 2021. — 471 p. Regression analysis of cause effect relationships is increasingly the core of medical and health research. This work is a 2nd edition of a 2017 pretty complete textbook and tutorial for students as well as recollection / update bench and help desk for professionals. It came to the authors' attention, that information of history,...
Cham: Springer, 2022. — 292 p. IBM (international business machines) has published in its SPSS statistical software 2022 update a very important novel regression method entitled Kernel Ridge Regression (KRR). It is an extension of the currently available regression methods, and is suitable for pattern recognition in high dimensional data, particularly, when alternative methods...
Cham: Springer, 2022. — 283 p. Quantile regression is an approach to data at a loss of homogeneity, for example (1) data with outliers, (2) skewed data like corona - deaths data, (3) data with inconstant variability, (4) big data. In clinical research many examples can be given like circadian phenomena, and diseases where spreading may be dependent on subsets with frailty, low...
2nd edition. — New York: Springer, 2021. — 471 p. Regression analysis of cause effect relationships is increasingly the core of medical and health research. This work is a 2nd edition of a 2017 pretty complete textbook and tutorial for students as well as recollection / update bench and help desk for professionals. It came to the authors' attention, that information of history,...
Boca Raton: CRC Press, 2024. — 448 p. Preface Notation and Definitions Authors List of Figures List of Tables Introduction Envelopes for Regression PLS Algorithms for Predictor Reduction Asymptotic Properties of PLS Simultaneous Reduction Partial PLS and Partial Envelopes Linear Discriminant Analysis Quadratic Discriminant Analysis Non-linear PLS The Role of PLS in Social...
Hoboken: Wiley, 1994. – 280 p. Covers the use of dynamic and interactive computer graphics in linear regression analysis, focusing on analytical graphics. Features new techniques like Description rotation. The authors have composed their own regression code, using Xlisp-Stat language called R-code, which is a nearly complete system for linear regression analysis and can be...
New York: The Guilford Press, 2017. — 689 p. — (Methodology in the Social Sciences). — ISBN: 9781462521135. Emphasizing conceptual understanding over mathematics, this user-friendly text introduces linear regression analysis to students and researchers across the social, behavioral, consumer, and health sciences. Coverage includes model construction and estimation,...
N.-Y.: Wiley, 2013. — 276 p. — ISBN: 978-1-119-97528-1. A guide to the implementation and interpretation of Quantile Regression models . This book explores the theory and numerous applications of quantile regression, offering empirical data analysis as well as the software tools to implement the methods. The main focus of this book is to provide the reader with a comprehensive...
3rd Edition. — John Wiley & Sons, Inc., 1998. — 736 p. — ISBN: 0-471-17082-8. An outstanding introduction to the fundamentals of regression analysis-updated and expanded The methods of regression analysis are the most widely used statistical tools for discovering the relationships among variables. This classic text, with its emphasis on clear, thorough presentation of concepts...
New York: W. H. Freeman, 1976. — 244 p. Linear Relationships Some Simple Nonlinear Relationships, that can be Transformed into Linear Relationships The Regression Line of Y on X The Correlation Coefficient Correlation and Regression with Standartized Variables Factors Influencing the Magnitude of the Correlation Coefficient Special Cases of the Correlation Coefficient Tests of...
Los Angeles: SAGE, 2017. — 817 p. Linear models, their variants, and extensions—the most important of which are generalized linear models—are among the most useful and widely used statistical tools for social general research. This book aims to provide an accessible, in-depth, modern treatment of regression analysis, linear models, generalized linear models, and closely related...
2nd edition. — Philadelphia: SAGE Publications, 2020. — 315 p. Regression diagnostics are methods for determining whether a regression model that has been fit to data adequately represents the structure of the data. For example, if the model assumes a linear (straight-line) relationship between the response and an explanatory variable, is the assumption of linearity warranted?...
Newbury Park: Sage Publications, Inc, 1991. — 100 p. — ISBN: 080393971X, 978-0803939714.
Series: Quantitative Applications in the Social Sciences (Book 79).
Книга посвящена неизменно возникающим в ходе применения регрессионного анализа проблемам, обусловленным нарушениями предположений метода наименьших квадратов, выявлению таких нарушений, борьбе с их вредным влиянием и...
2nd ed. — Springer, 2015. — 598 p. — (Springer Series in Statistics). — ISBN 9783319194240, EISBN 9783319194257. This highly anticipated second edition features new chapters and sections, 225 new references, and comprehensive R software. In keeping with the previous edition, this book is about the art and science of data analysis and predictive modelling, which entails choosing...
Ann Arbor: The University of Michigan Press, 2007. — 160 p. Social scientists study complex phenomena about which they often propose intricate hypotheses tested with linear-interactive or multiplicative terms. While interaction terms are hardly new to social science research, researchers have yet to develop a common methodology for using and interpreting them. Modeling and...
2nd Edition. — Elsevier Inc., 2006. — 480 pages ISBN: 0120885972 The book provides complete coverage of the classical methods of statistical analysis. It is designed to give students an understanding of the purpose of statistical analyses, to allow the student to determine, at least to some degree, the correct type of statistical analyses to be performed in a given situation,...
Б.м.: Jim Frost, 2019. — 340 p. My Approach to Teaching Regression and Statistics Correlation and an Introduction to Regression Graph Your Data to Find Correlations Interpret the Pearson’s Correlation Coefficient Examples of Positive and Negative Correlations Graphs for Different Correlations Discussion about the Correlation Scatterplots Pearson’s Correlation Measures Linear...
Wiley, 2018. — 299 p. — ISBN: 978-1-118-86360-2. Contains an overview of several technical topics of Quantile Regression Volume two of Quantile Regression offers an important guide for applied researchers that draws on the same example-based approach adopted for the first volume. The text explores topics including robustness, expectiles, m-quantile, decomposition, time series,...
Statistical Associates Publishers, 2014. — 224 p. — ISBN9781626380240. An illustrated tutorial and introduction to binary and multinomial logistic regression using SPSS, SAS, or Stata for examples. Suitable for introductory graduate-level study. The 2014 edition is a major update to the 2012 edition. Among the new features are these: Over 80 additional pages of coverage (224 pages...
Third Edition. — McGraw-Hill Education, 2016. — 1472 p. — ISBN: 978-0-07-182411-8. A textbook on the use of advanced statistical methods in healthcare sciences. This book is a textbook especially created for medical, public health, and social and environmental science students who need applied (not theoretical) training in the use of statistical methods. The book has been...
WIT Press, 2010. — 451 p. This book is an introduction to regression analysis for upper division and graduate students in science, engineering, social science and medicine. The emphasis is on the classical linear regression diagnostics, ridge and logistic regression are treated as well. In contrast to other books at this level, the theoretical foundation of the subject is...
Springer, 2003. — 399 p. In linear regression the ordinary least squares estimator plays a central role and sometimes one may get the impression that it is the only reasonable and applicable estimator available. Nonetheless, there exists a variety of alterna tives, proving useful in specific situations. Purpose and Scope. This book aims at presenting a comprehensive survey of...
Boca Raton: CRC Press;Taylor and Francis, 2017. — 423 p. Regression Analysis and Its Application: A Data-Oriented Approach answers the need for researchers and students who would like a better understanding of classical regression analysis. Useful either as a textbook or as a reference source, this book bridges the gap between the purely theoretical coverage of regression analysis...
6th Edition. — John Wiley & Sons, Inc., 2023. — 480 p. — (Wiley Series in Probability and Statistics). — ISBN: 978-1119830887. In the newly revised sixth edition of Regression Analysis By Example Using R, distinguished statistician Dr Ali S. Hadi delivers an expanded and thoroughly updated discussion of exploratory data analysis using regression analysis in R. The book provides...
Cambridge University Press, 1992 — 434 p. — ISBN: 0521429501.
This book concentrates on the statistical aspects of nonparametric regression smoothing from an applied point of view. The methods covered in this text can be used in biometry, econometrics, engineering and mathematics. The two central problems discussed are the choice of smoothing parameter and the construction of...
Sage Publications, Inc, 1993. — 100 p. It is often necessary for social scientists to study differences in groups, such as gender or race differences in attitudes, buying behavior, or socioeconomic characteristics. When the researcher seeks to estimate group differences through the use of independent variables that are qualitative, dummy variables allow the researcher to...
New York: Springer, 2015. — 582 p. This highly anticipated second edition features new chapters and sections, 225 new references, and comprehensive R software. In keeping with the previous edition, this book is about the art and science of data analysis and predictive modeling, which entails choosing and using multiple tools. Instead of presenting isolated techniques, this text...
2nd ed. — Springer, 2015. — 597 p. — (Springer Series in Statistics). — ISBN: 9783319194240, 9783319194257 This highly anticipated second edition features new chapters and sections, 225 new references, and comprehensive R software. In keeping with the previous edition, this book is about the art and science of data analysis and predictive modeling, which entails choosing and...
Corrected Edition. — N.-Y.: Springer, 2001. — 571 p. — ISBN: 0387952322, 978-0387952321. Many texts are excellent sources of knowledge about individual statistical tools, but the art of data analysis is about choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasizes problem solving strategies that address the many issues arising when...
Springer, 2015. — 240 p. — ISBN: 9783319125282, 9783319125299 This unique book explains how to fashion useful regression models from commonly available data to erect models essential for evidence-based road safety management and research. Composed from techniques and best practices presented over many years of lectures and workshops, The Art of Regression Modeling in Road...
Boca Raton: CRC Press, 2009. — 637 p. This text presents an overview of the full range of logistic models, including binary, proportional, ordered, and categorical response regression procedures. It illustrates how to apply the models to medical, health, environmental/ecological, physical, and social science data. Stata is used to develop, evaluate, and display most models...
2nd edition. — Cambridge University Press, 2011. — 572 p. — ISBN: 0521198151, 9780521198158. This second edition of Hilbe's Negative Binomial Regression is a substantial enhancement to the popular first edition. The only text devoted entirely to the negative binomial model and its many variations, nearly every model discussed in the literature is addressed. The theoretical and...
Second Edition. — Wiley, 2003. — 741 p. A popular statistical text now updated and better than ever! The ready availability of high-speed computers and statistical software encourages the analysis of ever larger and more complex problems while at the same time increasing the likelihood of improper usage. That is why it is increasingly important to educate end users in the correct...
Provo: Brigham Young University, 2010. — 285 p. I have been teaching these methods for several years and have seen many students struggle and more succeed. Thus, I know how important it is that students are familiar with some standard statistical concepts before beginning to learn about linear regression analysis. Hence, the first chapter is designed as a quick and dirty review...
Boca Raton: CRC Press, 2022. — 437 p. Research in social and behavioral sciences has benefited from linear regression models (LRMs) for decades to identify and understand the associations among a set of explanatory variables and an outcome variable. Linear Regression Models: Applications in R provides you with a comprehensive treatment of these models and indispensable guidance...
University of California Press, 2016. — 579 p. Social science and behavioral science students and researchers are often confronted with data that are categorical, count a phenomenon, or have been collected over time. Sociologists examining the likelihood of interracial marriage, political scientists studying voting behavior, criminologists counting the number of offenses people...
CRC Press, 2022. — 437 p. — ISBN 9780367753665. Research in social and behavioral sciences has benefited from linear regression models (LRMs) for decades to identify and understand the associations among a set of explanatory variables and an outcome variable. Linear Regression Models: Applications in R provides you with a comprehensive treatment of these models and...
2nd ed, 2000.
Introduction to the Logistic Regression Model.
Multiple Logistic Regression.
Interpretation of the Fitted Logistic Regression Model.
Model-Building Strategies and Methods for Logistic Regression.
Assessing the Fit of the Model.
Application of Logistic Regression with Different Sampling Models.
Logistic Regression for Matched Case-Control Studies.
Special...
Wiley, 2013. — 528 p. — 3rd ed. — ISBN: 0470582472, 9780470582473. A new edition of the definitive guide to logistic regression modeling for health science and other applications. This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a...
Nova Science Publishers, 2018. — 343 p. — ISBN: 9781536137989. Aims to present both conventional and fuzzy regression analyses from theoretical aspects followed by application examples. The present book contains chapters originating from different scientific fields. The first deals with both crisp (conventional) linear or nonlinear regression and fuzzy linear or nonlinear...
Newbury Park: SAGE Publications, Inc, 1987. — 102 p. The second edition of this book provides a conceptual understanding of analysis of variance. It outlines methods for analysing variance that are used to study the effect of one or more nominal variables on a dependent, interval level variable. The book presumes only elementary background in significance testing and data...
New York: Routledge, 2017. — 530 p. Alan Jones' practical guide to the robust but often misunderstood techniques of Linear and Non-Linear Regression in the context of estimating. The text considers Simple Linear Regression and ask what is it doing?, how good is it?, how accurate is it? and how can we use it to create estimates? Not all estimating relationships are linear, but if...
Boca Raton: CRC Press, 2023. — 298 p. Modern Applied Regressions creates an intricate and colorful mural with mosaics of categorical and limited response variable (CLRV) models using both Bayesian and Frequentist approaches. Written for graduate students, junior researchers, and quantitative analysts in behavioral, health, and social sciences, this text provides details for...
3rd edition. — New York: Routledge, 2019. — 654 p. Multiple Regression and Beyond offers a conceptually-oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods. By focusing on the concepts and purposes of MR and related methods, rather than the derivation and calculation of...
New York: Springer, 2010. — 709 p. Like previous editions, this textbook provides a highly readable description of fundamental and more advanced concepts and methods of logistic regression. It is suitable for researchers and statisticians in medical and other life sciences as well as academicians teaching second-level regression methods courses.;The Computer Appendix provides...
Second Edition: Chapman and Hall/CRC, 2014.— 425 p. — ISBN: 9781466584495 An Up-to-Date, All-in-One Resource for Using SAS and R to Perform Frequent Tasks. The first edition of this popular guide provided a path between SAS and R using an easy-to-understand, dictionary-like approach. Retaining the same accessible format, SAS and R: Data Management, Statistical Analysis, and...
Springer, 2012. — 244 p. — ISBN: 1461405734, 9781461405733. Presents four central topics in stochastic optimization: calculation of parameter estimates, the asymptotic theory of estimates, estimation theory for small samples, and prediction theory Describes applications to practical problems from various areas of study including econometrics, clinical medicine, and several...
Cambridge, Cambridge University Press, 2005. Econometric Society Monograph Series. ISBN: 9780521608275. 366 pages. 63 b/w illus. 13 tables 20 exercises. Quantile regression is gradually emerging as a unified statistical methodology for estimating models of conditional quantile functions. This monograph is the first comprehensive treatment of the subject, encompassing models...
Boca Raton: CRC Press, 2018. — 485 p. Quantile regression constitutes an ensemble of statistical techniques intended to estimate and draw inferences about conditional quantile functions. Median regression, as introduced in the 18th century by Boscovich and Laplace, is a special case. In contrast to conventional mean regression that minimizes sums of squared residuals, median...
Boca Raton: CRC Press, 2019. — 325 p. Advanced Regression Models with SAS and Rexposes the reader to the modern world of regression analysis. The material covered by this book consists of regression models that go beyond linear regression, including models for right-skewed, categorical and hierarchical observations. The book presents the theory as well as fully worked-out...
Peter James Kpolovie, 2021. — 463 p. — ISBN 979-8-5958-4025-5. Корреляция, множественная регрессия Это превосходное руководство IBM SPSS предназначено для установления взаимосвязей между переменными, включая чисто причинно-следственные связи, и для точного прогнозирования событий. Существование зависит от отношений. Каждый пользователь этой книги может без труда установить...
Peter James Kpolovie, 2021. — 463 p. — ISBN 979-8-5958-4025-5. Корреляция, множественная регрессия Это превосходное руководство IBM SPSS предназначено для установления взаимосвязей между переменными, включая чисто причинно-следственные связи, и для точного прогнозирования событий. Существование зависит от отношений. Каждый пользователь этой книги может без труда установить...
McGraw-Hill, 2004. — 1396 p. — (Operations and Decision Sciences). — ISBN 0-07-238688-6. This new edition of Applied Linear Statistical Models retains the book's uniquely straightforward writing style and format while providing you with the latest information and knowledge. Updates include developments and methods in partial regression and residual plots, an entirely new...
Philadelphia: Sage Publications, Inc, 1980. — 80 p. Applied regression allows social scientists who are not specialists in quantitative techniques to arrive at clear verbal explanations of their numerical results. Provides a lucid discussion of more specialized subjects: analysis of residuals, interaction effects, specification error, multicollinearity, standardized...
Minneapolis: University of Minnesota, 2016. — 82 p. What is Linear Regression Model What is R What’s next Missing Values Sanity Checking & Data Cleaning Example Data Data Frames Accessing a Data Frame Visualize the Data The Linear Model Function Evaluating Quality of the Model Residual Analysis Visualizing the Relationships in the Data Identifying Potential Predictors Backward...
CRC Press, Taylor & Francis Group, 2011. — 269 p. — ISBN: 978-1439828090. Simultaneous confidence bands enable more intuitive and detailed inference of regression analysis than the standard inferential methods of parameter estimation and hypothesis testing. Simultaneous Inference in Regression provides a thorough overview of the construction methods and applications of...
Iowa City: SAGE Publications, 2002. — 80 p. Spline Regression Models shows the nuts-and-bolts of using dummy variables to formulate and estimate various spline regression models. For some researchers this will involve situations where the number and location of the spline knots are known in advance, while others will need to determine the number and location of spline knots as...
SAGE Publications, 2022. — 200 p. — (The SAGE Quantitative Research Kit). — ISBN 1526424177. Part of The SAGE Quantitative Research Kit , this text helps you make the crucial steps towards mastering multivariate analysis of social science data , introducing the fundamental linear and non-linear regression models used in quantitative research. Peter Martin covers both the theory...
Los Angeles: SAGE Publications, 2022. — 338 p. This text provides practical guidance on conducting regression analysis on categorical and count data. Step by step and supported by lots of helpful graphs, it covers both the theoretical underpinnings of these methods as well as their application, giving you the skills needed to apply them to your own research. It offers guidance...
Springer, 2023. — 286 p. — (International Series in Operations Research & Management Science 337). — ISBN 978-3-031-21479-0. Applied Linear Regression for Business Analytics with R introduces regression analysis to business students using the R programming language with a focus on illustrating and solving real-time, topical problems. Specifically, this book presents modern and...
B.: Springer, 2013. - 66p. Quantile regression analysis differs from more conventional regression models in its emphasis on distributions. Whereas standard regression procedures show how the expected value of the dependent variable responds to a change in an explanatory variable, quantile regressions imply predicted changes for the entire distribution of the dependent variable....
CRC Press, 2024. — 239 p. This book covers the main models within the GLM (i.e., logistic, Poisson, negative binomial, ordinal, and multinomial). For each model, estimations, interpretations, model fit, diagnostics, and how to convey results graphically are provided. There is a focus on graphic displays of results as these are a core strength of using R for statistical...
Pearson, 2012. — 816 p. — 7th ed. — ISBN: 0321748247, 0321691695, 9780321691699 This text is designed for two types of statistics courses. The early chapters, combined with a selection of the case studies, are designed for use in the second half of a two-semester (two-quarter) introductory statistics sequence for undergraduates with statistics or nonstatistics majors. Or, the...
7th Edition. — N.Y.: Prentice-Hall, 2011. — 812 p. This text is designed for two types of statistics courses. The early chapters, combined with a selection of the case studies, are designed for use in the second half of a two-semester (two-quarter) introductory statistics sequence for undergraduates. with statistics or nonstatistics majors. Or, the text can be used for a course...
8th Edition. — Pearson, 2020. — 844 p. — ISBN13: 978-0-13-516379-5. A Second Course in Statistics: Regression Analysis, 8th Edition is a highly readable text that explains concepts in a logical, intuitive manner with worked-out examples. Applications to engineering, sociology, psychology, science, and business are demonstrated throughout; real data and scenarios extracted from...
2nd ed. — Boca Raton: CRC, 2002. — 256 p. Originally published in 1990, the first edition of Subset Selection in Regression filled a significant gap in the literature, and its critical and popular success has continued for more than a decade. Thoroughly revised to reflect progress in theory, methods, and computing power, the second edition promises to continue that tradition....
2nd edition. — Stata Press, 2021. — 732 p. — ISBN 978-1-59718-322-2. Interpreting and Visualizing Regression Models Using Stata, Second Edition provides clear and simple examples illustrating how to interpret and visualize a wide variety of regression models. Including over 200 figures, the book illustrates linear models with continuous predictors (modeled linearly, using...
2nd ed. — Stata Corp, 2021. — 695 p. — ISBN 1597183210, 9781597183215, 1597183229, 9781597183222, 1597183237, 9781597183239, 2020950108. This book illustrates how to interpret and visualize the results of regression models using an example-based approach. The way we interpret the effect of a predictor depends on the nature of the predictor. For example, the strategy we use to...
New York: Chapman and Hall/CRC , 2018. — 136 p. A core task in statistical analysis, especially in the era of Big Data, is the fitting of flexible, high-dimensional, and non-linear models to noisy data in order to capture meaningful patterns. This can often result in challenging non-linear and non-convex global optimization problems. The large data volume that must be handled...
4th edition. — Hoboken: Wiley, 2006. — 370 p. A comprehensive and up-to-date introduction to the fundamentals of regression analysis The Fourth Edition of Introduction to Linear Regression Analysis describes both the conventional and less common uses of linear regression in the practical context of today's mathematical and scientific research. This popular book blends both theory...
5th Edition. — John Wiley & Sons, 2012.
A comprehensive and up-to-date introduction to the fundamentals of regression analysis.
Introduction to Linear Regression Analysis, Fifth Edition continues to present both the conventional and less common uses of linear regression in today's cutting-edge scientific research. The authors blend both theory and application to equip...
New Jersey: Wiley, 2012. — 836 p. — ISBN 978-0-470-54281-1. A comprehensive and up-to-date introduction to the fundamentals of regression analysis. Introduction to Linear Regression Analysis, Fifth Edition continues to present both the conventional and less common uses of linear regression in today’s cutting-edge scientific research. The authors blend both theory and...
San Diego: R.D. Irwin, 1983. - 561p.
The long established leading authoritative text and reference on regression. For students in most any discipline where statistical analysis or interpretation is used, ALRM has served as the industry standard. The text includes brief introductory and review material, and then proceeds through regression and modeling. All topics are presented...
Philadelphia: SAGE publications, 2005. — 121 p. Logistic Regression Models for Ordinal Response Variables provides applied researchers in the social, educational, and behavioral sciences with an accessible and comprehensive coverage of analyses for ordinal outcomes. The content builds on a review of logistic regression, and extends to details of the cumulative (proportional)...
Springer, 2017. — 494 p. This text covers both multiple linear regression and some experimental design models. The text uses the response plot to visualize the model and to detect outliers, does not assume that the error distribution has a known parametric distribution, develops prediction intervals that work when the error distribution is unknown, suggests bootstrap hypothesis...
New York: Springer, 2017. — 497 p. — ISBN: 978-3-319-55250-7. This text covers both multiple linear regression and some experimental design models. The text uses the response plot to visualize the model and to detect outliers, does not assume that the error distribution has a known parametric distribution, develops prediction intervals that work when the error distribution is...
Carbondale: David J. Olive, 2010. — 641 p. Regression is the study of the conditional distribution Y |x of the response Y given the p × 1 vector of nontrivial predictors x. In a 1D regression model, Y is conditionally independent of x given a single linear combination α + βTx of the predictors, written Y x|(α + βT x) or Y x|βTx. Many of the most used statistical methods are 1D...
SAGE Publications, Incorporated, 2016. — 489 p. In a conversational tone, Regression & Linear Modeling provides conceptual, user-friendly coverage of the generalized linear model (GLM). Readers will become familiar with applications of ordinary least squares (OLS) regression, binary and multinomial logistic regression, ordinal regression, Poisson regression, and loglinear...
2nd ed. — John Wiley & Sons, 2012. — 346 p. — ISBN: 1118097289. Fully revised to reflect the latest methodologies and emerging applications, Applied Regression Modeling, Second Edition continues to highlight the benefits of statistical methods, specifically regression analysis and modeling, for understanding, analyzing, and interpreting multivariate data in business, science,...
3rd edition. — Wiley, 2021. — 336 p. — ISBN 1119615860, 9781119615866. Master the fundamentals of regression without learning calculus with this one-stop resource The newly and thoroughly revised 3rd Edition of Applied Regression Modeling delivers a concise but comprehensive treatment of the application of statistical regression analysis for those with little or no background...
Springer, 2013. — 137 p. — ISBN: 9783642329302, e-ISBN: 9783642329319 — (Series: SpringerBriefs in Statistics). This is an unusual book because it contains a great deal of formulas. Hence it is a blend of monograph, textbook, and handbook. It is intended for students and researchers who need quick access to useful formulas appearing in the linear regression model and related...
Springer, 2001. — 659 p. — 2nd ed. — ISBN: 0387984542, 9780387984544 Least squares estimation, when used appropriately, is a powerful research tool. A deeper understanding of the regression concepts is essential for achieving optimal benefits from a least squares analysis. This book builds on the fundamentals of statistical methods and provides appropriate concepts that will...
New York: Springer, 2004. — 671 p. Least squares estimation, when used appropriately, is a powerful research tool. A deeper understanding of the regression concepts is essential for achieving optimal benefits from a least squares analysis. This book builds on the fundamentals of statistical methods and provides appropriate concepts that will allow a scientist to use least...
New York: Springer, 1998. - 258p. In the area of multivariate analysis, there are two broad themes that have emerged over time. The analysis typically involves exploring the variations in a set of interrelated variables or investigating the simultaneous relation ships between two or more sets of variables. In either case, the themes involve explicit modeling of the...
John Wiley & Sons Ltd., 2016. — 388 p. — ISBN: 9781118597965. Since mathematical models express our understanding of how nature behaves, we use them to validate our understanding of the fundamentals about systems (which could be processes, equipment, procedures, devices, or products). Also, when validated, the model is useful for engineering applications related to diagnosis,...
CRC Press, 2021. — 437 p. — ISBN 978-1-4398-8538-3. Beyond Multiple Linear Regression: Applied Generalized Linear Models and Multilevel Models in R is designed for undergraduate students who have successfully completed a multiple linear regression course, helping them develop an expanded modeling toolkit that includes non-normal responses and correlated structure. Even though...
Boca Raton: CRC Press, 2021. — 437 p. Beyond Multiple Linear Regression: Applied Generalized Linear Models and Multilevel Models in R is designed for undergraduate students who have successfully completed a multiple linear regression course, helping them develop an expanded modeling toolkit that includes non-normal responses and correlated structure. Even though there is no...
New York: BEP, 2016. — 215 p. This book creates a balance between the theory, practical applications, and computer implementation behind Regression—one of the most widely used techniques in analyzing and solving real world problems. It begins with a thorough explanation of prerequisite knowledge with a discussion of Simple Regression Analysis including the computer...
Wiley, 2019. — 363 p. — (Probability and Statistics). — ISBN: 9781118644614. A guide to the systematic analytical results for ridge, LASSO, preliminary test, and Stein-type estimators with applications This book 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...
Cambridge: Cambridge University Press, 2024. — 295 p. Linear regression analysis, with its many generalizations, is the predominant quantitative method used throughout the social sciences and beyond. The goal of the method is to study relations among variables. In this book, Schoon, Melamed and Breiger turn regression modeling inside out to put the emphasis on the cases...
Philadelphia: SAGE, 1986. — 85 p. The authors have provided beginners with a background to the frequently-used technique of linear regression. It is not intended to be a substitute for a course or textbook in statistics, but rather a stop-gap for students who encounter empirical work before undertaking a statistics course. It provides a heuristic explanation of the procedures and...
Wiley, 2003. — 582 p. — ISBN: 9780471415404 Concise, mathematically clear, and comprehensive treatment of the subject. Expanded coverage of diagnostics and methods of model fitting. Requires no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight-line regression and simple analysis of variance models. More than 200 problems throughout...
N.-Y.: Wiley, 2003. — 572 p. — ISBN: 0-471-41540-5. Второе, дополненное издание переведенной у нас монографии "Линейный регрессионный анализ". Concise, mathematically clear, and comprehensive treatment of the subject. * Expanded coverage of diagnostics and methods of model fitting. * Requires no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance...
Springer, 1990. — 360 p. — ISBN 1461287898, 9781461287896. An up-to-date, rigorous, and lucid treatment of the theory, methods, and applications of regression analysis, and thus ideally suited for those interested in the theory as well as those whose interests lie primarily with applications. It is further enhanced through real-life examples drawn from many disciplines, showing...
Boca Raton: CRC Press Taylor & Francis Group, 2014. — 200 p. — e-ISBN: 978-1-4200-9994-2. Series: Chapman & Hall/CRC Monographs on Statistics & Applied Probability (Book 132). Drawing on the authors' substantial expertise in modeling longitudinal and clustered data, Quasi-Least Squares Regression provides a thorough treatment of quasi-least squares (QLS) regression — a...
New York: Arcler Press, 2019. — 214 p. — ISBN10 1774071584. — ISBN13 978-1774071588. Correlation and Regression Analysis: Applications for Industrial Organizationsbook discusses the important theoretical concepts such as the Amortization System Constant, French System of Price Amortization, comparative analysis of these methods and American System of Amortization which provide...
Sebtel Press, 2022. - 139 p. - ISBN 191627918X. Linear regression is the workhorse of data analysis. It is the first step, and often the only step , in fitting a simple model to data. This brief book explains the essential mathematics required to understand and apply regression analysis. The tutorial style of writing, accompanied by over 30 diagrams, offers a visually intuitive...
N.-Y.: Springer. 2014. — 290 p. The standard approach of most introductory books for practical statistics is that readers first learn the minimum mathematical basics of statistics and rudimentary concepts of statistical methodology. They then are given examples of analyses of data obtained from natural and social phenomena so that they can grasp practical definitions of...
Springer. 2014. — 290 p. — ISBN: 4431543201. The standard approach of most introductory books for practical statistics is that readers first learn the minimum mathematical basics of statistics and rudimentary concepts of statistical methodology. They then are given examples of analyses of data obtained from natural and social phenomena so that they can grasp practical...
Boca Raton: CRC Press, 2022. — 249 p. This book introduces best practices in longitudinal data analysis at intermediate level, with a minimum number of formulas without sacrificing depths. It meets the need to understand statistical concepts of longitudinal data analysis by visualizing important techniques instead of using abstract mathematical formulas. Different solutions...
Routledge, 2020. — 198 p. — ISBN: 978-1-138-33547-9. This book is an introduction to regression analysis, focusing on the practicalities of doing regression analysis on real-life data. Contrary to other textbooks on regression, this book is based on the idea that you do not necessarily need to know much about statistics and mathematics to get a firm grip on regression and...
Routledge, 2020. — 198 p. — ISBN: 978-1-138-33547-9. This book is an introduction to regression analysis, focusing on the practicalities of doing regression analysis on real-life data. Contrary to other textbooks on regression, this book is based on the idea that you do not necessarily need to know much about statistics and mathematics to get a firm grip on regression and...
New York: Springer, 1994. — 151 p. — ISBN: 9780387942636. In many areas of science a basic task is to assess the influence of several factors on a quantity of interest. If this quantity is binary logistic, regression models provide a powerful tool for this purpose. This monograph presents an account of the use of logistic regression in the case where missing values in the...
Springer, 2018. — 473 p. This book expands on the classical statistical multivariate analysis theory by focusing on bilinear regression models, a class of models comprising the classical growth curve model and its extensions. In order to analyze the bilinear regression models in an interpretable way, concepts from linear models are extended and applied to tensor spaces....
Wiley, 2014. — 370 p. — 4th ed. — ISBN: 9781118386088 The Fourth Edition of Applied Linear Regression provides a thorough update of the basic theory and methodology of linear regression modeling. Demonstrating the practical applications of linear regression analysis techniques, the Fourth Edition uses interesting, real-world exercises and examples. Stressing central concepts...
CRC Press, 2020. — 514 p. — ISBN: 9780367458522. Understanding Regression Analysis unifies diverse regression applications including the classical model, ANOVA models, generalized models including Poisson, Negative binomial, logistic, and survival, neural networks, and decision trees under a common umbrella -- namely, the conditional distribution model. It explains why the...
CRC Press, 2020. — 514 p. — ISBN: 9780367458522. Understanding Regression Analysis unifies diverse regression applications including the classical model, ANOVA models, generalized models including Poisson, Negative binomial, logistic, and survival, neural networks, and decision trees under a common umbrella -- namely, the conditional distribution model. It explains why the...
CRC Press, 2020. — 514 p. — ISBN: 978-0-367-45852-2. Understanding Regression Analysis unifies diverse regression applications including the classical model, ANOVA models, generalized models including Poisson, Negative binomial, logistic, and survival, neural networks, and decision trees under a common umbrella — namely, the conditional distribution model. It explains why the...
CRC Press, 2020. — 514 p. — ISBN: 978-0-367-45852-2. Understanding Regression Analysis unifies diverse regression applications including the classical model, ANOVA models, generalized models including Poisson, Negative binomial, logistic, and survival, neural networks, and decision trees under a common umbrella — namely, the conditional distribution model. It explains why the...
Springer, 2024. — 288 p. This book reports the developments of the Total Least Square (TLS) algorithms for parameter estimation and adaptive filtering. Specifically, it introduces the authors’ latest achievements in the past 20 years, including the recursive TLS algorithms, the approximate inverse power iteration TLS algorithm, the neural based MCA algorithm, the neural based...
Yan X., Su X.G. Linear Regression Analysis: Theory and Computing World Scientific Publishing Co. Pte. Ltd. | 2009 | ISBN-10: 9812834109 | 349 pages by Xin Yan (University of Missouri–Kansas City, USA) & Xiao Gang Su (University of Central Florida, USA) This volume presents in detail the fundamental theories of linear regression analysis and diagnosis, as well as the relevant...
Иркутск : ИрГУПС, 2019. — 209 с. Монография посвящена построению регрессионных моделей с ошибками как в объясняемой, так и в объясняющих переменных. Исследованы вопросы применимости на практике простейшей однофакторной модели с ошибками в объясняющей переменной – регрессии Деминга. На основе регрессии Деминга разработаны и изучены модели парно-множественной и полносвязной...
Свердловск: Средне-Уральское кн. изд-во, 1976. - 44 с.
С позиций теории некорректных задач рассмотрена классическая схема регрессионного анализа. В результате предложена индуктивная процедура построении уравнения регрессии, пригодная для решения задач большой размерности.
Методические указания. — Оренбург: Оренбургский государственный университет (ОГУ), 2011. — 30 с. Методические указания к семинарским занятиям, лабораторному практикуму, самостоятельной работе студентов, в том числе для выполнения расчетно-графических заданий, курсовых и дипломных работ, связанных с регрессионным анализом. Предназначены для специальности 080116 – Математические...
М.: Финансы и статистика, 1987. — 239 с.
Книга систематизирует и обобщает новые направления регрессионного анализа, в том числе нарушения предпосылок (диагностика и пути преодоления), к которым относятся: нарушения предпосылки нормальности и нарушения однородности дисперсий. В качестве путей преодоления рассматриваются непараметрические методы оценивания, робастные методы...
Под ред. Адлера Ю.П. — М.: Финансы и статистика, 1987. — 230 с. Книга систематизирует и обобщает новые направления регрессионного анализа, в том числе нарушения предпосылок (диагностика и пути преодоления), к которым относятся: нарушения предпосылки нормальности и нарушения однородности дисперсий. В качестве путей преодоления рассматриваются непараметрические методы оценивания,...
М.: ДМК Пресс, 2022. — 750 с. Регрессия – это статистический метод, который позволяет найти уравнение, наилучшим образом описывающее совокупность данных. Регрессионный анализ позволяет моделировать, проверять и исследовать пространственные отношения, а в ряде случаев устанавливать причинно-следственные связи между независимыми и зависимыми переменными. В этой книге представлен...
М.: ДМК Пресс, 2022. — 750 с. Регрессия – это статистический метод, который позволяет найти уравнение, наилучшим образом описывающее совокупность данных. Регрессионный анализ позволяет моделировать, проверять и исследовать пространственные отношения, а в ряде случаев устанавливать причинно-следственные связи между независимыми и зависимыми переменными. В этой книге представлен...
М.: Финансы и статистика, 1981. — 304 с. Рассматриваются современные методы оценивания параметров в линейных и нелинейных регрессиях - оценивание в условиях ошибок измерения, устойчивое и др. Даются практические рекомендации нахождения оценок. Изучаются статистические свойства оценок, методы построения доверительных интервалов и проверки гипотез в линейных и нелинейных...
М.: Финансы и статистика, 1981. — 304 с. Рассматриваются современные методы оценивания параметров в линейных и нелинейных регрессиях - оценивание в условиях ошибок измерения, устойчивое и др. Даются практические рекомендации нахождения оценок. Изучаются статистические свойства оценок, методы построения доверительных интервалов и проверки гипотез в линейных и нелинейных...
В 2-х кн. М.: Финансы и статистика, 1986. — 366 с. Работа американских учёных посвящена регрессионному анализу, применяемому во всех отраслях народного хозяйства и научных исследованиях. Второе издание (1-е изд. перевода — 1973 г. — вышло в одной книге) значительно переработано и дополнено новыми алгоритмами и сравнением их достоинств. Книга 1 содержит классическое описание...
В 2-х кн. М.: Финансы и статистика, 1986. — 366 с. Работа американских учёных посвящена регрессионному анализу, применяемому во всех отраслях народного хозяйства и научных исследованиях. Второе издание (1-е изд. перевода — 1973 г. — вышло в одной книге) значительно переработано и дополнено новыми алгоритмами и сравнением их достоинств. Книга 1 содержит классическое описание...
М.: Московский университет МВД РФ им. В.Я. Кикотя, 2013. — 233 с. Учебное пособие ориентировано на углубленное изучение формальных методов теории вероятностей и математической статистики для анализа и прогнозирования, выявление конкретных количественных закономерностей и взаимосвязей объектов и процессов с помощью математических и статистических методов и моделей. Пособие...
Новосибирск: НГТУ, 2011. — 77 с. В учебном пособии рассматриваются методы выбора структуры одномерных (однооткликовых) регрессионных моделей и методы построения многомерных (многооткликовых) регрессионных моделей (оценивание параметров, проверка гипотез, выбор структуры). Большое внимание уделяется способам организации эффективных вычислений при переборе структур. Пособие...
Это перевод книги Montgomery D.C., Peck E.A. Introduction to Linear Regression Analysis. - New York: John Wiley & Sons, 1982. 504 p., которая является базовой по множественной регрессии и которая нужна для трех основных целей (при переводе устранены ошибки в формулах, это проверено на ряде тестовых данных). (1) Выявления связей изучаемой характеристики с рядом других, обычно более...
Это перевод книги Montgomery D.C., Peck E.A. Introduction to Linear Regression Analysis. - New York: John Wiley & Sons, 1982. 504 р., которая является базовой по множественной регрессии и которая нужна для трех основных целей (при переводе устранены ошибки в формулах, это проверено на ряде тестовых данных). (1) Выявления связей изучаемой характеристики с рядом других, обычно более...
Монография. — Иркутск: ИрГУПС, 2018. — 176 с. — ISBN: 978-5-98710-354-8. Монография посвящена одному из основных инструментов анализа данных — регрессионному анализу. Предложены новые способы решения проблем, возникающих на этапах спецификации, параметризации и верификации регрессионных моделей. В основе предлагаемых методик лежит аппарат математического программирования, в том...
Монография. — Иркутск: Иркутский государственный университет путей сообщения (ИрГУПС), 2018. — 176 с. — ISBN: 978-5-98710-354-8. Монография посвящена одному из основных инструментов анализа данных — регрессионному анализу. Предложены новые способы решения проблем, возникающих на этапах спецификации, параметризации и верификации регрессионных моделей. В основе предлагаемых...
М.: Финансы и статистика, 1982. — 199 с.
Рассматривается комплекс вопросов, связанных с обработкой статистических данных и оцениванием регрессионных коэффициентов. Приводится описание алгоритмов регрессионных моделей, их сравнительный анализ. Для исследователей в области статистики, биологии, медицины и т.д., занимающихся разработкой регрессионных моделей.
Пер. с англ. А. М. Кагана, В. М Калинина и К. П. Латышева. — Под ред. академика Ю. В. Линника. — Москва: Наука, 1968. — 548 с. Книга содержит восемь глав. В главе 1 изложены необходимые сведения из линейной алгебры, в главе 2 — из теории вероятностей. Статистическая часть начинается с главы 3, где описываются некоторые стандартные распределения математической статистики,...
Методические указания. — Оренбург: Оренбургский государственный университет (ОГУ), 2007. — 31 с. Методические указания содержат описание реализации регрессионного анализа средствами диалоговой системы STADIA и статистического пакета STATISTICA с последующим анализом результатов, а также индивидуальные занятия для лабораторной работы. Методические указания предназначены для...
М.: ДМК Пресс, 2014. — 222 с. — ISBN: 978-5-97060-115-0. Риса и Миу учатся в институте и подрабатывают в кафе Norns. Миу очень нравится один из посетителей кафе, но она не знает, как с ним познакомиться. Однажды он забывает на столе книгу, которая оказывается учебником по регрессионному анализу. Теперь есть повод заговорить с ним, но Миу почти не знакома с регрессионным...
М.: ДМК Пресс, 2014. — 222 с. — ISBN: 978-5-97060-115-0. Риса и Миу учатся в институте и подрабатывают в кафе Norns. Миу очень нравится один из посетителей кафе, но она не знает, как с ним познакомиться. Однажды он забывает на столе книгу, которая оказывается учебником по регрессионному анализу. Теперь есть повод заговорить с ним, но Миу почти не знакома с регрессионным...
М.: Мир, 1993. — 349 с. Книга посвящена новому развивающемуся разделу математической статистики, содержит основные идеи теории и дает обзор современных подходов к практическому решению вопроса о скрытых (от "наблюдателя") зависимостей в имеющихся данных. Книга содержит богатый материал по приложениям, доведенный до описания пакетов программ для персональных компьютеров. Для...
Saarbrücken: Lambert Academic Publishing, 2017. — 128 с. В учебном пособии рассмотрены основные инструменты, используемые для регрессионного анализа данных в аналитическом приложении Deductor Studio: линейная регрессия, декомпозиция временного ряда и логистическая регрессия. Приведены примеры, позволяющие получить навыки их практического применения в бизнес-аналитике. Учебное...
Учебное пособие. — Волгоград: Волгоградский государственный технический университет, 2015. — 64 с. — ISBN: 978–5–9948–2003–2/ Пособие содержит теоретические основы регрессионного моделирования и подробные рекомендации по его выполнению в пакете STATISTICA, дополненные вспомогательными материалами, примерами и задачами. Учебное пособие предназначено для студентов старших курсов...
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