Download or read book Multiple Hypotheses Testing in the Linear Regression Model with Applications to Economics and Finance written by Raimund Alt and published by Cuvillier Verlag. This book was released on 2005 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Linear Regression and Its Application to Economics written by Zdzisław Hellwig and published by Elsevier. This book was released on 2014-05-12 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear Regression and its Application to Economics presents the economic applications of regression theory. This book discusses the importance of linear regression for multi-dimensional variables. Organized into six chapters, this book begins with an overview of the elementary concepts and the more important definitions and theorems concerning two-dimensional and multi-dimensional random variables. This text then examines the important applications of correlation methods to economics. Other chapters consider the methods of estimating regression parameters. This book discusses as well the methods of testing some statistical hypotheses relevant for practical applications of the correlation analysis. The final chapter deals with the fact that correlation methods can be used not only in static but also in dynamic research. This book is a valuable resource for scientists in economic, agricultural, and technical colleges who deal with economic problems in their research. Graduates of economic and technical colleges employed in different branches of the national economy will also find this book useful.
Download or read book Business Applications of Multiple Regression Second Edition written by Ronny Richardson and published by Business Expert Press. This book was released on 2015-01-14 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition of Business Applications of Multiple Regression describes the use of the statistical procedure called multiple regression in business situations, including forecasting and understanding the relationships between variables. The book assumes a basic understanding of statistics but reviews correlation analysis and simple regression to prepare the reader to understand and use multiple regression. The techniques described in the book are illustrated using both Microsoft Excel and a professional statistical program. Along the way, several real-world data sets are analyzed in detail to better prepare the reader for working with actual data in a business environment. This book will be a useful guide to managers at all levels who need to understand and make decisions based on data analysis performed using multiple regression. It also provides the beginning analyst with the detailed understanding required to use multiple regression to analyze data sets.
Download or read book The Linear Regression Model Under Test written by W. Kraemer and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph grew out of joint work with various dedicated colleagues and students at the Vienna Institute for Advanced Studies. We would probably never have begun without the impetus of Johann Maurer, who for some time was the spiritus rector behind the Institute's macromodel of the Austrian economy. Manfred Deistler provided sustained stimulation for our research through many discussions in his econometric research seminar. Similar credits are due to Adrian Pagan, Roberto Mariano and Garry Phillips, the econometrics guest professors at the Institute in the 1982 - 1984 period, who through their lectures and advice have contributed greatly to our effort. Hans SchneeweiB offered helpful comments on an earlier version of the manuscript, and Benedikt Poetscher was always willing to lend a helping . hand when we had trouble with the mathematics of the tests. Needless to say that any errors are our own. Much of the programming for the tests and for the Monte Carlo experiments was done by Petr Havlik, Karl Kontrus and Raimund Alt. Without their assistance, our research project would have been impossible. Petr Havlik and Karl Kontrus in addition. read and criticized portions of the manuscript, and were of great help in reducing our error rate. Many of the more theoretical results in this monograph would never have come to light without the mathematical expertise of Werner Ploberger, who provided most of the statistical background of the chapter on testing for structural change . .
Download or read book Applied Regression Analysis for Business written by Jacek Welc and published by Springer. This book was released on 2017-12-29 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers hands-on statistical tools for business professionals by focusing on the practical application of a single-equation regression. The authors discuss commonly applied econometric procedures, which are useful in building regression models for economic forecasting and supporting business decisions. A significant part of the book is devoted to traps and pitfalls in implementing regression analysis in real-world scenarios. The book consists of nine chapters, the final two of which are fully devoted to case studies. Today's business environment is characterised by a huge amount of economic data. Making successful business decisions under such data-abundant conditions requires objective analytical tools, which can help to identify and quantify multiple relationships between dozens of economic variables. Single-equation regression analysis, which is discussed in this book, is one such tool. The book offers a valuable guide and is relevant in various areas of economic and business analysis, including marketing, financial and operational management.
Download or read book Testing Research Hypotheses Using Multiple Linear Regression written by Keith A. McNeil and published by . This book was released on 1975 with total page 618 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple regression is becomingmore widely used as the statistical technique for answering research hypotheses. This is so for several reasons: 1) the technique is extremely versatile; 2) the computer has made the technique more available to researchers; and 3) texts such as the authors' earlier work are making the technique more available to researchers. The statistical technique of multiple regression allows the inclusion of numerous continuous (quantitative) and categorical (qualitative) variables in the prediction of some criterion. Appendixes contain a multiple regression computer program and data on which the problems are based; a discussion of the similarities and differences between analysis of variance and multiple regression; and a computer program providing the regression solution to natural language research hypotheses.
Download or read book Regression Modeling with Actuarial and Financial Applications written by Edward W. Frees and published by Cambridge University Press. This book was released on 2010 with total page 585 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book teaches multiple regression and time series and how to use these to analyze real data in risk management and finance.
Download or read book Econometric Methods with Applications in Business and Economics written by C. Heij and published by Oxford University Press. This book was released on 2004-03-25 with total page 814 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nowadays applied work in business and economics requires a solid understanding of econometric methods to support decision-making. Combining a solid exposition of econometric methods with an application-oriented approach, this rigorous textbook provides students with a working understanding and hands-on experience of current econometrics. Taking a 'learning by doing' approach, it covers basic econometric methods (statistics, simple and multiple regression, nonlinear regression, maximum likelihood, and generalized method of moments), and addresses the creative process of model building with due attention to diagnostic testing and model improvement. Its last part is devoted to two major application areas: the econometrics of choice data (logit and probit, multinomial and ordered choice, truncated and censored data, and duration data) and the econometrics of time series data (univariate time series, trends, volatility, vector autoregressions, and a brief discussion of SUR models, panel data, and simultaneous equations). • Real-world text examples and practical exercise questions stimulate active learning and show how econometrics can solve practical questions in modern business and economic management. • Focuses on the core of econometrics, regression, and covers two major advanced topics, choice data with applications in marketing and micro-economics, and time series data with applications in finance and macro-economics. • Learning-support features include concise, manageable sections of text, frequent cross-references to related and background material, summaries, computational schemes, keyword lists, suggested further reading, exercise sets, and online data sets and solutions. • Derivations and theory exercises are clearly marked for students in advanced courses. This textbook is perfect for advanced undergraduate students, new graduate students, and applied researchers in econometrics, business, and economics, and for researchers in other fields that draw on modern applied econometrics.
Download or read book Multiple Test Procedures and the Closure Principle written by Raimund Alt and published by . This book was released on 1991 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Understanding Regression Analysis written by Larry D. Schroeder and published by SAGE Publications. This book was released on 2016-10-20 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding Regression Analysis: An Introductory Guide presents the fundamentals of regression analysis, from its meaning to uses, in a concise, easy-to-read, and non-technical style. It illustrates how regression coefficients are estimated, interpreted, and used in a variety of settings within the social sciences, business, law, and public policy. Packed with applied examples and using few equations, the book walks readers through elementary material using a verbal, intuitive interpretation of regression coefficients, associated statistics, and hypothesis tests. The Second Edition features updated examples and new references to modern software output.
Download or read book Simplified Machine Learning written by Dr. Pooja Sharma and published by BPB Publications. This book was released on 2024-06-15 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the world of Artificial Intelligence with a deep understanding of Machine Learning concepts and algorithms KEY FEATURES ● A detailed study of mathematical concepts, Machine Learning concepts, and techniques. ● Discusses methods for evaluating model performances and interpreting results. ● Explores all types of Machine Learning (supervised, unsupervised, reinforcement, association rule mining, artificial neural network) in detail. ● Comprises numerous review questions and programming exercises at the end of every chapter. DESCRIPTION "Simplified Machine Learning" is a comprehensive guide that navigates readers through the intricate landscape of Machine Learning, offering a balanced blend of theory, algorithms, and practical applications. The first section introduces foundational concepts such as supervised and unsupervised learning, regression, classification, clustering, and feature engineering, providing a solid base in Machine Learning theory. The second section explores algorithms like decision trees, support vector machines, and neural networks, explaining their functions, strengths, and limitations, with a special focus on deep learning, reinforcement learning, and ensemble methods. The book also covers essential topics like model evaluation, hyperparameter tuning, and model interpretability. The final section transitions from theory to practice, equipping readers with hands-on experience in deploying models, building scalable systems, and understanding ethical considerations. By the end, readers will be able to leverage Machine Learning effectively in their respective fields, armed with practical skills and a strategic approach to problem-solving. WHAT YOU WILL LEARN ● Solid foundation in Machine Learning principles, algorithms, and methodologies. ● Implementation of Machine Learning models using popular libraries like NumPy, Pandas, PyTorch, or scikit-learn. ● Knowledge about selecting appropriate models, evaluating their performance, and tuning hyperparameters. ● Techniques to pre-process and engineer features for Machine Learning models. ● To frame real-world problems as Machine Learning tasks and apply appropriate techniques to solve them. WHO THIS BOOK IS FOR This book is designed for a diverse audience interested in Machine Learning, a core branch of Artificial Intelligence. Its intellectual coverage will benefit students, programmers, researchers, educators, AI enthusiasts, software engineers, and data scientists. TABLE OF CONTENTS 1. Introduction to Machine Learning 2. Data Pre-processing 3. Supervised Learning: Regression 4. Supervised Learning: Classification 5. Unsupervised Learning: Clustering 6. Dimensionality Reduction and Feature Selection 7. Association Rule Mining 8. Artificial Neural Network 9. Reinforcement Learning 10. Project Appendix Bibliography
Download or read book Multiple Hypothesis Testing written by Houston Nash Gilbert and published by . This book was released on 2009 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Conservation Laws and Symmetry Applications to Economics and Finance written by Ryuzo Sato and published by Springer Science & Business Media. This book was released on 1990-05-31 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modem geometric methods combine the intuitiveness of spatial visualization with the rigor of analytical derivation. Classical analysis is shown to provide a foundation for the study of geometry while geometrical ideas lead to analytical concepts of intrinsic beauty. Arching over many subdisciplines of mathematics and branching out in applications to every quantitative science, these methods are, notes the Russian mathematician A.T. Fomenko, in tune with the Renais sance traditions. Economists and finance theorists are already familiar with some aspects of this synthetic tradition. Bifurcation and catastrophe theo ries have been used to analyze the instability of economic models. Differential topology provided useful techniques for deriving results in general equilibrium analysis. But they are less aware of the central role that Felix Klein and Sophus Lie gave to group theory in the study of geometrical systems. Lie went on to show that the special methods used in solving differential equations can be classified through the study of the invariance of these equations under a continuous group of transformations. Mathematicians and physicists later recognized the relation between Lie's work on differential equations and symme try and, combining the visions of Hamilton, Lie, Klein and Noether, embarked on a research program whose vitality is attested by the innumerable books and articles written by them as well as by biolo gists, chemists and philosophers.
Download or read book The Basics of Financial Econometrics written by Frank J. Fabozzi and published by John Wiley & Sons. This book was released on 2014-03-04 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible guide to the growing field of financial econometrics As finance and financial products have become more complex, financial econometrics has emerged as a fast-growing field and necessary foundation for anyone involved in quantitative finance. The techniques of financial econometrics facilitate the development and management of new financial instruments by providing models for pricing and risk assessment. In short, financial econometrics is an indispensable component to modern finance. The Basics of Financial Econometrics covers the commonly used techniques in the field without using unnecessary mathematical/statistical analysis. It focuses on foundational ideas and how they are applied. Topics covered include: regression models, factor analysis, volatility estimations, and time series techniques. Covers the basics of financial econometrics—an important topic in quantitative finance Contains several chapters on topics typically not covered even in basic books on econometrics such as model selection, model risk, and mitigating model risk Geared towards both practitioners and finance students who need to understand this dynamic discipline, but may not have advanced mathematical training, this book is a valuable resource on a topic of growing importance.
Download or read book Multiple Regression and Analysis of Variance written by George O. Wesolowsky and published by New York ; Toronto : Wiley. This book was released on 1976 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Essentials of Econometrics written by Damodar N. Gujarati and published by McGraw-Hill Companies. This book was released on 1992 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to econometrics and its applications. The text emphasizes the intuition behind econometric analysis and contains examples from economics, finance, marketing and management to explain concepts.
Download or read book Parametric Statistical Change Point Analysis written by Jie Chen and published by Springer Science & Business Media. This book was released on 2011-11-06 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This revised and expanded second edition is an in-depth study of the change point problem from a general point of view, as well as a further examination of change point analysis of the most commonly used statistical models. Change point problems are encountered in such disciplines as economics, finance, medicine, psychology, signal processing, and geology, to mention only several. More recently, change point analysis has been found in extensive applications related to analyzing biomedical imaging data and gene expression data. Extensive examples throughout the text emphasize key concepts and different methodologies used. New examples of change point analysis in modern molecular biology and other fields such as finance and air traffic control have been added to this second edition.