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Building Regression Models With Sas


Building Regression Models With Sas
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Advanced Regression Models With Sas And R


Advanced Regression Models With Sas And R
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Author : Olga Korosteleva
language : en
Publisher: CRC Press
Release Date : 2018-12-07

Advanced Regression Models With Sas And R written by Olga Korosteleva and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-07 with Mathematics categories.


Advanced Regression Models with SAS and R exposes 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 numerical examples with complete SAS and R codes for each regression. The emphasis is on model accuracy and the interpretation of results. For each regression, the fitted model is presented along with interpretation of estimated regression coefficients and prediction of response for given values of predictors. Features: Presents the theoretical framework for each regression. Discusses data that are categorical, count, proportions, right-skewed, longitudinal and hierarchical. Uses examples based on real-life consulting projects. Provides complete SAS and R codes for each example. Includes several exercises for every regression. Advanced Regression Models with SAS and R is designed as a text for an upper division undergraduate or a graduate course in regression analysis. Prior exposure to the two software packages is desired but not required. The Author: Olga Korosteleva is a Professor of Statistics at California State University, Long Beach. She teaches a large variety of statistical courses to undergraduate and master’s students. She has published three statistical textbooks. For a number of years, she has held the position of faculty director of the statistical consulting group. Her research interests lie mostly in applications of statistical methodology through collaboration with her clients in health sciences, nursing, kinesiology, and other fields.



Building Regression Models With Sas


Building Regression Models With Sas
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Author : Robert N. Rodriguez
language : en
Publisher: SAS Institute
Release Date : 2023-04-18

Building Regression Models With Sas written by Robert N. Rodriguez and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-18 with Computers categories.


Advance your skills in building predictive models with SAS! Building Regression Models with SAS: A Guide for Data Scientists teaches data scientists, statisticians, and other analysts who use SAS to train regression models for prediction with large, complex data. Each chapter focuses on a particular model and includes a high-level overview, followed by basic concepts, essential syntax, and examples using new procedures in both SAS/STAT and SAS Viya. By emphasizing introductory examples and interpretation of output, this book provides readers with a clear understanding of how to build the following types of models: general linear models quantile regression models logistic regression models generalized linear models generalized additive models proportional hazards regression models tree models models based on multivariate adaptive regression splines Building Regression Models with SAS is an essential guide to learning about a variety of models that provide interpretability as well as predictive performance.



Predictive Modeling With Sas Enterprise Miner


Predictive Modeling With Sas Enterprise Miner
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Author : Kattamuri S. Sarma
language : en
Publisher: SAS Institute
Release Date : 2017-07-20

Predictive Modeling With Sas Enterprise Miner written by Kattamuri S. Sarma and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-20 with Computers categories.


« Written for business analysts, data scientists, statisticians, students, predictive modelers, and data miners, this comprehensive text provides examples that will strengthen your understanding of the essential concepts and methods of predictive modeling. »--



Building Better Models With Jmp Pro


Building Better Models With Jmp Pro
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Author : Jim Grayson
language : en
Publisher: SAS Institute
Release Date : 2015-08

Building Better Models With Jmp Pro written by Jim Grayson and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-08 with Computers categories.


Explore the black box of business analytics and learn the methodology for managing and executing analytics projects.



Exploring Modern Regression Methods Using Sas


Exploring Modern Regression Methods Using Sas
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Author :
language : en
Publisher:
Release Date : 2019-06-21

Exploring Modern Regression Methods Using Sas written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-21 with categories.


This special collection of SAS Global Forum papers demonstrates new and enhanced capabilities and applications of lesser-known SAS/STAT and SAS Viya procedures for regression models. The goal here is to raise awareness of current valuable SAS/STAT content of which the user may not be aware. Also available free as a PDF from sas.com/books.



Fundamentals Of Predictive Analytics With Jmp Second Edition


Fundamentals Of Predictive Analytics With Jmp Second Edition
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Author : Ron Klimberg
language : en
Publisher: SAS Institute
Release Date : 2017-12-19

Fundamentals Of Predictive Analytics With Jmp Second Edition written by Ron Klimberg and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-19 with Mathematics categories.


Written for students in undergraduate and graduate statistics courses, as well as for the practitioner who wants to make better decisions from data and models, this updated and expanded second edition of Fundamentals of Predictive Analytics with JMP(R) bridges the gap between courses on basic statistics, which focus on univariate and bivariate analysis, and courses on data mining and predictive analytics. Going beyond the theoretical foundation, this book gives you the technical knowledge and problem-solving skills that you need to perform real-world multivariate data analysis. First, this book teaches you to recognize when it is appropriate to use a tool, what variables and data are required, and what the results might be. Second, it teaches you how to interpret the results and then, step-by-step, how and where to perform and evaluate the analysis in JMP . Using JMP 13 and JMP 13 Pro, this book offers the following new and enhanced features in an example-driven format: an add-in for Microsoft Excel Graph Builder dirty data visualization regression ANOVA logistic regression principal component analysis LASSO elastic net cluster analysis decision trees k-nearest neighbors neural networks bootstrap forests boosted trees text mining association rules model comparison With today’s emphasis on business intelligence, business analytics, and predictive analytics, this second edition is invaluable to anyone who needs to expand his or her knowledge of statistics and to apply real-world, problem-solving analysis. This book is part of the SAS Press program.



Sas System For Regression


Sas System For Regression
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Author : Rudolf Freund
language : en
Publisher: John Wiley & Sons
Release Date : 2000-12-29

Sas System For Regression written by Rudolf Freund 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 2000-12-29 with Mathematics categories.


SAS® System for Regression Learn to perform a wide variety of regression analyses using SAS® software with this example-driven revised favorite from SAS Publishing. With this Third Edition you will learn the basics of performing regression analyses using a wide variety of models including nonlinear models. Other topics covered include performing linear regression analyses using PROC REG diagnosing and providing remedies for data problems, including outliers and multicollinearity. Examples feature numerous SAS procedures including REG, PLOT, GPLOT, NLIN, RSREG, AUTOREG, PRINCOMP, and others. A helpful discussion of theory is supplied where necessary. Some knowledge of both regression and the SAS System are assumed. New for this edition The Third Edition includes revisions, updated material, and new material. You’ll find new information on using SAS/INSIGHT® software regression with a binary response with emphasis on PROC LOGISTIC nonparametric regression (smoothing) using moving averages and PROC LOESS. Additionally, updated material throughout the book includes high-resolution PROC REG graphics output, using the OUTEST option to produce a data set, and using PROC SCORE to predict another data set.



Simulating Data With Sas


Simulating Data With Sas
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Author : Rick Wicklin
language : en
Publisher: SAS Institute
Release Date : 2013-04-22

Simulating Data With Sas written by Rick Wicklin and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-22 with Computers categories.


Data simulation is a fundamental technique in statistical programming and research. Rick Wicklin's Simulating Data with SAS brings together the most useful algorithms and the best programming techniques for efficient data simulation in an accessible how-to book for practicing statisticians and statistical programmers. This book discusses in detail how to simulate data from common univariate and multivariate distributions, and how to use simulation to evaluate statistical techniques. It also covers simulating correlated data, data for regression models, spatial data, and data with given moments. It provides tips and techniques for beginning programmers, and offers libraries of functions for advanced practitioners. As the first book devoted to simulating data across a range of statistical applications, Simulating Data with SAS is an essential tool for programmers, analysts, researchers, and students who use SAS software. This book is part of the SAS Press program.



Applied Linear Models With Sas


Applied Linear Models With Sas
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Author : Daniel Zelterman
language : en
Publisher: Cambridge University Press
Release Date : 2010-05-10

Applied Linear Models With Sas written by Daniel Zelterman 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 2010-05-10 with Medical categories.


This textbook for a second course in basic statistics for undergraduates or first-year graduate students introduces linear regression models and describes other linear models including Poisson regression, logistic regression, proportional hazards regression, and nonparametric regression. Numerous examples drawn from the news and current events with an emphasis on health issues illustrate these concepts. Assuming only a pre-calculus background, the author keeps equations to a minimum and demonstrates all computations using SAS. Most of the programs and output are displayed in a self-contained way, with an emphasis on the interpretation of the output in terms of how it relates to the motivating example. Plenty of exercises conclude every chapter. All of the datasets and SAS programs are available from the book's website, along with other ancillary material.



Sas For Finance


Sas For Finance
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Author : Harish Gulati
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-05-30

Sas For Finance written by Harish Gulati and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-30 with Computers categories.


Leverage the analytical power of SAS to perform financial analysis efficiently Key Features Leverage the power of SAS to analyze financial data with ease Find hidden patterns in your data, predict future trends, and optimize risk management Learn why leading banks and financial institutions rely on SAS for financial analysis Book Description SAS is a groundbreaking tool for advanced predictive and statistical analytics used by top banks and financial corporations to establish insights from their financial data. SAS for Finance offers you the opportunity to leverage the power of SAS analytics in redefining your data. Packed with real-world examples from leading financial institutions, the author discusses statistical models using time series data to resolve business issues. This book shows you how to exploit the capabilities of this high-powered package to create clean, accurate financial models. You can easily assess the pros and cons of models to suit your unique business needs. By the end of this book, you will be able to leverage the true power of SAS to design and develop accurate analytical models to gain deeper insights into your financial data. What you will learn Understand time series data and its relevance in the financial industry Build a time series forecasting model in SAS using advanced modeling theories Develop models in SAS and infer using regression and Markov chains Forecast inflation by building an econometric model in SAS for your financial planning Manage customer loyalty by creating a survival model in SAS using various groupings Understand similarity analysis and clustering in SAS using time series data Who this book is for Financial data analysts and data scientists who want to use SAS to process and analyze financial data and find hidden patterns and trends from it will find this book useful. Prior exposure to SAS will be helpful but is not mandatory. Some basic understanding of the financial concepts is required.