regression equations

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Seemingly Unrelated Regression Equations Models

Author : Virendera K. Srivastava
ISBN : 0824776100
Genre : Mathematics
File Size : 52. 73 MB
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The seemingly unrelated regression equations model; The least squares estimator and its variants; Approximate destribution theory for feasible generalized least squares estimators; Exact finite-sample properties of feasible generalized least squares estimators; Iterative estimators; Shrinkage estimators; Autoregressive disturbances; Heteroscedastic disturbances; Constrained error covariance structures; Prior information; Some miscellaneous topics.

Regression Equations For Estimating Concentrations Of Selected Water Quality Constituents For Selected Gaging Stations In The Red River Of The North Basin North Dakota Minnesota And South Dakota

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ISBN : 9781428984516
Genre :
File Size : 31. 92 MB
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Multiple Regression

Author : Leona S. Aiken
ISBN : 0761907122
Genre : Business & Economics
File Size : 23. 67 MB
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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 multiple regression to estimate models, or for those enrolled in courses on multivariate statistics.

Introduction To Nonparametric Regression

Author : K. Takezawa
ISBN : 9780471771449
Genre : Mathematics
File Size : 65. 48 MB
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An easy-to-grasp introduction to nonparametric regression This book's straightforward, step-by-step approach provides anexcellent introduction to the field for novices of nonparametricregression. Introduction to Nonparametric Regression clearlyexplains the basic concepts underlying nonparametric regression andfeatures: * Thorough explanations of various techniques, which avoid complexmathematics and excessive abstract theory to help readersintuitively grasp the value of nonparametric regressionmethods * Statistical techniques accompanied by clear numerical examplesthat further assist readers in developing and implementing theirown solutions * Mathematical equations that are accompanied by a clearexplanation of how the equation was derived The first chapter leads with a compelling argument for studyingnonparametric regression and sets the stage for more advanceddiscussions. In addition to covering standard topics, such askernel and spline methods, the book provides in-depth coverage ofthe smoothing of histograms, a topic generally not covered incomparable texts. With a learning-by-doing approach, each topical chapter includesthorough S-Plus? examples that allow readers to duplicate the sameresults described in the chapter. A separate appendix is devoted tothe conversion of S-Plus objects to R objects. In addition, eachchapter ends with a set of problems that test readers' grasp of keyconcepts and techniques and also prepares them for more advancedtopics. This book is recommended as a textbook for undergraduate andgraduate courses in nonparametric regression. Only a basicknowledge of linear algebra and statistics is required. Inaddition, this is an excellent resource for researchers andengineers in such fields as pattern recognition, speechunderstanding, and data mining. Practitioners who rely onnonparametric regression for analyzing data in the physical,biological, and social sciences, as well as in finance andeconomics, will find this an unparalleled resource.

Basic Principles Of Structural Equation Modeling

Author : Ralph O. Mueller
ISBN : 0387945164
Genre : Social Science
File Size : 27. 38 MB
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During the last two decades, structural equation modeling (SEM) has emerged as a powerful multivariate data analysis tool in social science research settings, especially in the fields of sociology, psychology, and education. Although its roots can be traced back to the first half of this century, when Spearman (1904) developed factor analysis and Wright (1934) introduced path analysis, it was not until the 1970s that the works by Karl Joreskog and his associates (e. g. , Joreskog, 1977; Joreskog and Van Thillo, 1973) began to make general SEM techniques accessible to the social and behavioral science research communities. Today, with the development and increasing avail ability of SEM computer programs, SEM has become a well-established and respected data analysis method, incorporating many of the traditional analysis techniques as special cases. State-of-the-art SEM software packages such as LISREL (Joreskog and Sorbom, 1993a,b) and EQS (Bentler, 1993; Bentler and Wu, 1993) handle a variety of ordinary least squares regression designs as well as complex structural equation models involving variables with arbitrary distributions. Unfortunately, many students and researchers hesitate to use SEM methods, perhaps due to the somewhat complex underlying statistical repre sentation and theory. In my opinion, social science students and researchers can benefit greatly from acquiring knowledge and skills in SEM since the methods-applied appropriately-can provide a bridge between the theo retical and empirical aspects of behavioral research.

Environmental Hydrology Second Edition

Author : Andy D. Ward
ISBN : 1566706165
Genre : Science
File Size : 30. 27 MB
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The technological advances of recent years include the emergence of new remote sensing and geographic information systems that are invaluable for the study of wetlands, agricultural land, and land use change. Students, hydrologists, and environmental engineers are searching for a comprehensive hydrogeologic overview that supplements information on hydrologic processes with data on these new information technology tools. Environmental Hydrology, Second Edition builds upon the foundation of the bestselling first edition by providing a qualitative understanding of hydrologic processes while introducing new methods for quantifying hydrologic parameters and processes. Written by authors with extensive multidisciplinary experience, the text first discusses the components of the hydrologic cycle, then follows with chapters on precipitation, stream processes, human impacts, new information system applications, and numerous other methods and strategies. By updating this thorough text with the newest analytical tools and measurement methodologies in the field, the authors provide an ideal reference for students and professionals in environmental science, hydrology, soil science, geology, ecological engineering, and countless other environmental fields.

Lisrel Approaches To Interaction Effects In Multiple Regression

Author : James Jaccard
ISBN : 0803971796
Genre : Social Science
File Size : 64. 62 MB
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With detailed examples, this book demonstrates the use of the computer program LISREL and how it can be applied to the analysis of interactions in regression frameworks. The authors consider a wide range of applications including: qualitative moderator variables; longitudinal designs; and product term analysis. They describe different types of measurement error and then present a discussion of latent variable representations of measurement error which serves as the foundation for the analyses described in later chapters. Finally they offer a brief introduction to LISREL and show how it can be used to execute the analyses. Readers can use this book without any prior training in LISREL and will find it an excellent introduction to analytic methods that deal with the problem of measurement error in the analysis of interactions.

Use Of Linear Regression Equations To Estimate Minimum Temperatures Over Peninsular Florida

Author : Warren R. Wallis
ISBN : OCLC:1244906
Genre : Atmospheric temperature forecasting
File Size : 48. 48 MB
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Applied Multiple Regression Correlation Analysis For The Behavioral Sciences

Author : Jacob Cohen
ISBN : 9781134801015
Genre : Psychology
File Size : 67. 6 MB
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This classic text on multiple regression is noted for its nonmathematical, applied, and data-analytic approach. Readers profit from its verbal-conceptual exposition and frequent use of examples. The applied emphasis provides clear illustrations of the principles and provides worked examples of the types of applications that are possible. Researchers learn how to specify regression models that directly address their research questions. An overview of the fundamental ideas of multiple regression and a review of bivariate correlation and regression and other elementary statistical concepts provide a strong foundation for understanding the rest of the text. The third edition features an increased emphasis on graphics and the use of confidence intervals and effect size measures, and an accompanying website with data for most of the numerical examples along with the computer code for SPSS, SAS, and SYSTAT, at www.psypress.com/9780805822236 . Applied Multiple Regression serves as both a textbook for graduate students and as a reference tool for researchers in psychology, education, health sciences, communications, business, sociology, political science, anthropology, and economics. An introductory knowledge of statistics is required. Self-standing chapters minimize the need for researchers to refer to previous chapters.

Correlation And Regression Analysis

Author : Thomas J. Archdeacon
ISBN : 029913654X
Genre : Social Science
File Size : 45. 92 MB
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In Correlation and Regression Analysis: A Historian's Guide Thomas J. Archdeacon provides historians with a practical introduction to the use of correlation and regression analysis. The book concentrates on the kinds of analysis that form the broad range of statistical methods used in the social sciences. It enables historians to understand and to evaluate critically the quantitative analyses that they are likely to encounter in journal literature and monographs reporting research findings in the social sciences. Without attempting to be a text in basic statistics, the book provides enough background information to allow readers to grasp the essentials of correlation and regression. Correlation analysis refers to the measurement of association between or among variables, and regression analysis focuses primarily on the use of linear models to predict changes in the value taken by one variable in terms of changes in the values of a set of explanatory variables. The book also discusses diagnostic methods for identifying shortcomings in regression models, the use of regression to analyze causation, and the application of regression and related procedures to the study of problems containing categorical as well as numerical data. Archdeacon asserts that knowing how statistical procedures are computed can clarify the theoretical structures underlying them and is essential for recognizing the conditions under which their use is appropriate. The book does not shy away from the mathematics of statistical analysis; but Archdeacon presents concepts carefully and explains the operation of equations step by step. Unlike many works in the field, the book does not assume that readers have mathematical training beyond basic algebra and geometry. In the hope of promoting the role of quantitative analysis in his discipline, Archdeacon discusses the theory and methods behind the most important interpretive paradigm for quantitative research in the social sciences. Correlation and Regression Analysis introduces statistical techniques that are indispensable to historians and enhances the presentation of them with practical examples from scholarly works.

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