Foundations Of Econometrics Using Sas R Simulations And Examples
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Foundations Of Econometrics Using Sas R Simulations And Examples
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Author : Anton Bekkerman
language : en
Publisher: Wiley-Blackwell
Release Date : 2017-07-10
Foundations Of Econometrics Using Sas R Simulations And Examples written by Anton Bekkerman and has been published by Wiley-Blackwell this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-10 with categories.
Sas Programming For R Users
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Author : Jordan Bakerman
language : en
Publisher:
Release Date : 2019-12-09
Sas Programming For R Users written by Jordan Bakerman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-09 with Computers categories.
SAS Programming for R Users, based on the free SAS Education course of the same name, is designed for experienced R users who want to transfer their programming skills to SAS. Emphasis is on programming and not statistical theory or interpretation. You will learn how to write programs in SAS that replicate familiar functions and capabilities in R. This book covers a wide range of topics including the basics of the SAS programming language, how to import data, how to create new variables, random number generation, linear modeling, Interactive Matrix Language (IML), and many other SAS procedures. This book also explains how to write R code directly in the SAS code editor for seamless integration between the two tools. Exercises are provided at the end of each chapter so that you can test your knowledge and practice your programming skills.
Statistical Foundations Of Econometric Modelling
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Author : Aris Spanos
language : en
Publisher: Cambridge University Press
Release Date : 1986-10-30
Statistical Foundations Of Econometric Modelling written by Aris Spanos and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986-10-30 with Business & Economics categories.
A thorough foundation in probability theory and statistical inference provides an introduction to the underlying theory of econometrics that motivates the student at a intuitive as well as a formal level.
Applied Econometrics With Sas
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Author : Barry K. Goodwin
language : en
Publisher: SAS Institute
Release Date : 2018-04-04
Applied Econometrics With Sas written by Barry K. Goodwin and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-04 with Computers categories.
Using Applied Econometrics with SAS: Modeling Demand, Supply, and Risk, you will quickly master SAS applications for implementing and estimating standard models in the field of econometrics. This guide introduces you to the major theories underpinning applied demand and production economics. For each of its three main topics—demand, supply, and risk—a concise theoretical orientation leads directly into consideration of specific economic models and econometric techniques, collectively covering the following: Double-log demand systems Linear expenditure systems Almost ideal demand systems Rotterdam models Random parameters logit demand models Frequency-severity models Compound distribution models Cobb-Douglas production functions Translogarithmic cost functions Generalized Leontief cost functions Density estimation techniques Copula models SAS procedures that facilitate estimation of demand, supply, and risk models include the following, among others: PROC MODEL PROC COPULA PROC SEVERITY PROC KDE PROC LOGISTIC PROC HPCDM PROC IML PROC REG PROC COUNTREG PROC QLIM An empirical example, SAS programming code, and a complete data set accompany each econometric model, empowering you to practice these techniques while reading. Examples are drawn from both major scholarly studies and business applications so that professors, graduate students, government economic researchers, agricultural analysts, actuaries, and underwriters, among others, will immediately benefit. This book is part of the SAS Press program.
Panel Data Econometrics With R
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Author : Yves Croissant
language : en
Publisher: John Wiley & Sons
Release Date : 2018-11-05
Panel Data Econometrics With R written by Yves Croissant and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-05 with Mathematics categories.
Panel Data Econometrics with R provides a tutorial for using R in the field of panel data econometrics. Illustrated throughout with examples in econometrics, political science, agriculture and epidemiology, this book presents classic methodology and applications as well as more advanced topics and recent developments in this field including error component models, spatial panels and dynamic models. They have developed the software programming in R and host replicable material on the book’s accompanying website.
Applied Econometrics Using The Sas System
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Author : Vivek Ajmani
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-20
Applied Econometrics Using The Sas System written by Vivek Ajmani and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-20 with Mathematics categories.
The first cutting-edge guide to using the SAS® system for the analysis of econometric data Applied Econometrics Using the SAS® System is the first book of its kind to treat the analysis of basic econometric data using SAS®, one of the most commonly used software tools among today's statisticians in business and industry. This book thoroughly examines econometric methods and discusses how data collected in economic studies can easily be analyzed using the SAS® system. In addition to addressing the computational aspects of econometric data analysis, the author provides a statistical foundation by introducing the underlying theory behind each method before delving into the related SAS® routines. The book begins with a basic introduction to econometrics and the relationship between classical regression analysis models and econometric models. Subsequent chapters balance essential concepts with SAS® tools and cover key topics such as: Regression analysis using Proc IML and Proc Reg Hypothesis testing Instrumental variables analysis, with a discussion of measurement errors, the assumptions incorporated into the analysis, and specification tests Heteroscedasticity, including GLS and FGLS estimation, group-wise heteroscedasticity, and GARCH models Panel data analysis Discrete choice models, along with coverage of binary choice models and Poisson regression Duration analysis models Assuming only a working knowledge of SAS®, this book is a one-stop reference for using the software to analyze econometric data. Additional features include complete SAS® code, Proc IML routines plus a tutorial on Proc IML, and an appendix with additional programs and data sets. Applied Econometrics Using the SAS® System serves as a relevant and valuable reference for practitioners in the fields of business, economics, and finance. In addition, most students of econometrics are taught using GAUSS and STATA, yet SAS® is the standard in the working world; therefore, this book is an ideal supplement for upper-undergraduate and graduate courses in statistics, economics, and other social sciences since it prepares readers for real-world careers.
Using Sas For Econometrics
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Author : R. Carter Hill
language : en
Publisher: Wiley Global Education
Release Date : 2012-04-13
Using Sas For Econometrics written by R. Carter Hill and has been published by Wiley Global Education this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-04-13 with Business & Economics categories.
A supplement such as Using SAS for Econometrics is quite essential for use in a classroom environment, for those attempting to learn SAS, and for quick and useful reference. The SAS documentation comes in many volumes, and several are thousands of pages long. This makes for a very difficult challenge when getting started with SAS. This volume spans several levels of econometrics. It is suitable for undergraduate students who will use canned SAS statistical procedures, and for graduate students who will use advanced procedures as well as direct programming in SAS's matrix language, discussed in chapter appendices. Material within the chapters is accessible to undergraduate and/or Masters students, with appendices to chapters devoted to more advanced materials and matrix programming.
Business Survival Analysis Using Sas
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Author : Jorge Ribeiro
language : en
Publisher:
Release Date : 2017
Business Survival Analysis Using Sas written by Jorge Ribeiro and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Business categories.
Solve business problems involving time-to-event and resulting probabilities by following the modeling tutorials in Business Survival Analysis Using SAS(R) An Introduction to Lifetime Probabilities, the first book to be published in the field of business survival analysis Survival analysis is a challenge. Books applying to health sciences exist, but nothing about survival applications for business has been available until now. Written for analysts, forecasters, econometricians, and modelers who work in marketing or credit risk and have little SAS modeling experience, Business Survival Analysis Using SAS(R) builds on a foundation of SAS code that works in any survival model and features numerous annotated graphs, coefficients, and statistics linked to real business situations and data sets. This guide also helps recent graduates who know the statistics but do not necessarily know how to apply them get up and running in their jobs. By example, it teaches the techniques while avoiding advanced theoretical underpinnings so that busy professionals can rapidly deliver a survival model to meet common business needs. From first principles, this book teaches survival analysis by highlighting its relevance to business cases. A pragmatic introduction to survival analysis models, it leads you through business examples that contextualize and motivate the statistical methods and SAS coding. Specifically, it illustrates how to build a time-to-next-purchase survival model in SAS(R) Enterprise Miner, and it relates each step to the underlying statistics and to Base SAS(R) and SAS/STAT(R) software. Following the many examples "from data preparation to validation to scoring new customers "you will learn to develop and apply survival analysis techniques to scenarios faced by companies in the financial services, insurance, telecommunication, and marketing industries, including the following scenarios: Time-to-next-purchase for marketing Employer turnover for human resources Small business portfolio macroeconometric stress tests for banks International Financial Reporting Standard (IFRS 9) lifetime probability of default for banks and building societies "Churn," or attrition, models for the telecommunications and insurance industries
Multilevel Modeling Methods With Introductory And Advanced Applications
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Author : Ann A. O'Connell
language : en
Publisher: IAP
Release Date : 2022-03-01
Multilevel Modeling Methods With Introductory And Advanced Applications written by Ann A. O'Connell and has been published by IAP this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-01 with Education categories.
Multilevel Modeling Methods with Introductory and Advanced Applications provides a cogent and comprehensive introduction to the area of multilevel modeling for methodological and applied researchers as well as advanced graduate students. The book is designed to be able to serve as a textbook for a one or two semester course in multilevel modeling. The topics of the seventeen chapters range from basic to advanced, yet each chapter is designed to be able to stand alone as an instructional unit on its respective topic, with an emphasis on application and interpretation. In addition to covering foundational topics on the use of multilevel models for organizational and longitudinal research, the book includes chapters on more advanced extensions and applications, such as cross-classified random effects models, non-linear growth models, mixed effects location scale models, logistic, ordinal, and Poisson models, and multilevel mediation. In addition, the volume includes chapters addressing some of the most important design and analytic issues including missing data, power analyses, causal inference, model fit, and measurement issues. Finally, the volume includes chapters addressing special topics such as using large-scale complex sample datasets, and reporting the results of multilevel designs. Each chapter contains a section called Try This!, which poses a structured data problem for the reader. We have linked our book to a website (http://modeling.uconn.edu) containing data for the Try This! section, creating an opportunity for readers to learn by doing. The inclusion of the Try This! problems, data, and sample code eases the burden for instructors, who must continually search for class examples and homework problems. In addition, each chapter provides recommendations for additional methodological and applied readings.
The R Software
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Author : Pierre Lafaye de Micheaux
language : en
Publisher: Springer Science & Business
Release Date : 2014-05-13
The R Software written by Pierre Lafaye de Micheaux and has been published by Springer Science & Business this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-13 with Computers categories.
The contents of The R Software are presented so as to be both comprehensive and easy for the reader to use. Besides its application as a self-learning text, this book can support lectures on R at any level from beginner to advanced. This book can serve as a textbook on R for beginners as well as more advanced users, working on Windows, MacOs or Linux OSes. The first part of the book deals with the heart of the R language and its fundamental concepts, including data organization, import and export, various manipulations, documentation, plots, programming and maintenance. The last chapter in this part deals with oriented object programming as well as interfacing R with C/C++ or Fortran, and contains a section on debugging techniques. This is followed by the second part of the book, which provides detailed explanations on how to perform many standard statistical analyses, mainly in the Biostatistics field. Topics from mathematical and statistical settings that are included are matrix operations, integration, optimization, descriptive statistics, simulations, confidence intervals and hypothesis testing, simple and multiple linear regression, and analysis of variance. Each statistical chapter in the second part relies on one or more real biomedical data sets, kindly made available by the Bordeaux School of Public Health (Institut de Santé Publique, d'Épidémiologie et de Développement - ISPED) and described at the beginning of the book. Each chapter ends with an assessment section: memorandum of most important terms, followed by a section of theoretical exercises (to be done on paper), which can be used as questions for a test. Moreover, worksheets enable the reader to check his new abilities in R. Solutions to all exercises and worksheets are included in this book.