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...
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...
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...
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...
2nd ed. — CRC Press, 2024. — 670 p. — (Chapman & Hall/CRC Texts in Statistical Science). — ISBN 1498755569. Generalized Linear Mixed Models: Modern Concepts, Methods, and Applications (2nd edition) presents an updated introduction to linear modeling using the generalized linear mixed model (GLMM) as the overarching conceptual framework. For students new to statistical modeling,...
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...
Sage Publications, 2024. — 205 p. Log-linear, logit and logistic regression models are the most common ways of analyzing data when (at least) the dependent variable is categorical. This volume shows how to compare coefficient estimates from regression models for categorical dependent variables in three typical research situations: (i) within one equation, (ii) between identical...
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...
School of Mathematics & Statistics The University of Melbourne. August 2016, 201 p. The thesis presents a model of the outstanding balance on a credit card account in which purchases and payments the card-holder makes follow marks. point processes. We use the model of credit card balance to derive an account-level model of profitability that incorporates ongoing sources of...
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...
Chapman and Hall/CRC, 2024. — 144 p. — ISBN: 978-1-003-39882-0. Statistics is central in the biosciences, social sciences and other disciplines, yet many students often struggle to learn how to perform statistical tests, and to understand how and why statistical tests work. Although there are many approaches to teaching statistics, a common framework exists between them:...
Chapman and Hall/CRC, 2024. — 144 p. — ISBN: 978-1-003-39882-0. Statistics is central in the biosciences, social sciences and other disciplines, yet many students often struggle to learn how to perform statistical tests, and to understand how and why statistical tests work. Although there are many approaches to teaching statistics, a common framework exists between them:...
Chapman and Hall/CRC, 2024. — 144 p. — ISBN: 978-1-003-39882-0. Statistics is central in the biosciences, social sciences and other disciplines, yet many students often struggle to learn how to perform statistical tests, and to understand how and why statistical tests work. Although there are many approaches to teaching statistics, a common framework exists between them:...
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...
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...
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...
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...
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...
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....