Practical Time Series Analysis Using SAS [Perfect Paperback]Anders Milhoj (Author) Book Description[size=0.86em]Publication Date: April 1 2013 | ISBN-10: 1612901700 | ISBN-13: 978-1612901701
Anders Milhøj's Practical Time Series Analysis Using SAS explains and demonstrates through examples how you can use SAS for time series analysis. It offers modern procedures for forecasting, seasonal adjustments, and decomposition of time series that can be used without involved statistical reasoning. The book teaches, with numerous examples, how to apply these procedures with very simple coding. In addition, it also gives the statistical background for interested readers. Beginning with an introductory chapter that covers the practical handling of time series data in SAS using the TIMESERIES and EXPAND procedures, it goes on to explain forecasting, which is found in the ESM procedure; seasonal adjustment, including trading-day correction using PROC X12; and unobserved component models using PROC UCM.
[1000求书]Segmentation and Lifetime Value Models Using SAS
[size=0.86em]Segmentation and Lifetime Value Models Using SAS [Perfect Paperback]Edward C. Malthouse (Author) Be the first to review this item Book Description[size=0.86em]Publication Date: May 23 2013 | ISBN-10: 1612906966 | ISBN-13: 978-1612906966
Help your organization determine the value of its customer relationships with Segmentation and Lifetime Value Models Using SAS. This book contains a wealth of information that will help you perform analyses to identify your customers and make informed marketing investments. It answers core questions on customer relationship management (CRM) and provides an overall framework for thinking about CRM and offering real-world examples across a variety of industries. Edward C. Malthouse introduces you to a number of useful models, ranging from simple to more complicated examples, and discusses their applications. You'll learn about segmentation models for identifying groups of customers and about lifetime value models for estimating the future value of the segments. You'll learn how to prepare data and estimate models using Base SAS, SAS/STAT, SAS/IML, and SQL. Marketing analysts, CRM analysts, database managers, and anyone looking to address the challenges of allocating marketing resources to different customer groups will benefit from the concepts and exercises in this book. Analysts will learn how to approach unique business problems. Managers will gain a sense of what's possible and what to ask of their analytics departments.
Product Details
Perfect Paperback: 182 pages
Publisher: SAS Institute (May 23 2013)
Language: English
ISBN-10: 1612906966
ISBN-13: 978-1612906966
Product Dimensions: 1 x 21.3 x 27.5 cm
Shipping Weight: 458 g
Simulating Data with SAS [Perfect Paperback]Rick Wicklin (Author)
Book Description[size=0.86em]Publication Date: May 15 2013 | ISBN-10: 1612903320 | ISBN-13: 978-1612903323
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.
[1000求书]Time Series Analysis by State Space Methods: Second Edition
Time Series Analysis by State Space Methods: Second Edition (Oxford Statistical Science Series)
Product DescriptionReviewReview from previous edition: "...provides an up-to-date exposition and comprehensive treatment of state space models in time series analysis...This book will be helpful to graduate students and applied statisticians working in the area of econometric modelling as well as researchers in the areas of engineering, medicine and biology where state space models are used." --Journal of the Royal Statistical Society
Product DescriptionThis new edition updates Durbin & Koopman's important text on the state space approach to time series analysis. The distinguishing feature of state space time series models is that observations are regarded as made up of distinct components such as trend, seasonal, regression elements and disturbance terms, each of which is modelled separately. The techniques that emerge from this approach are very flexible and are capable of handling a much wider range of problems than the
main analytical system currently in use for time series analysis, the Box-Jenkins ARIMA system. Additions to this second edition include the filtering of nonlinear and non-Gaussian series.
Part I of the book obtains the mean and variance of the state, of a variable intended to measure the effect of an interaction and of regression coefficients, in terms of the observations.
Part II extends the treatment to nonlinear and non-normal models. For these, analytical solutions are not available so methods are based on simulation.
Simulating Data with SAS [Perfect Paperback]Rick Wicklin (Author)
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