\u003cb\u003eTo use statistical methods and SAS applications to forecast the future values of data taken over time, you need only follow this thoroughly updated classic on the subject.\u003c/b\u003e With this third edition of \u003ci\u003eSAS for Forecasting Time Series\u003c/i\u003e, intermediate-to-advanced SAS usersâsuch as statisticians, economists, and data scientistsâcan now match the most sophisticated forecasting methods to the most current SAS applications.\n\u003cp\u003e\nStarting with fundamentals, this new edition presents methods for modeling both univariate and multivariate data taken over time. From the well-known ARIMA models to unobserved components, methods that span the range from simple to complex are discussed and illustrated. Many of the newer methods are variations on the basic ARIMA structures.\n\u003cp\u003e\nCompletely updated, this new edition includes fresh, interesting business situations and data sets, and new sections on these up-to-date statistical methods:\n\u003cp\u003e\u003cul\u003e\n\u003cli\u003eARIMA models \n\u003cli\u003eVector autoregressive models\n\u003cli\u003eExponential smoothing models\n\u003cli\u003eUnobserved component and state-space models\n\u003cli\u003eSeasonal adjustment\n\u003cli\u003eSpectral analysis\u003c/ul\u003e\n\u003cp\u003e\nFocusing on application, this guide teaches a wide range of forecasting techniques by example. The examples provide the statistical underpinnings necessary to put the methods into practice. The following up-to-date SAS applications are covered in this edition:\n\u003cp\u003e\u003cul\u003e\n\u003cli\u003eThe ARIMA procedure\n\u003cli\u003eThe AUTOREG procedure\n\u003cli\u003eThe VARMAX procedure\n\u003cli\u003eThe ESM procedure\n\u003cli\u003eThe UCM and SSM procedures\n\u003cli\u003eThe X13 procedure\n\u003cli\u003eThe SPECTRA procedure\n\u003cli\u003eSAS Forecast Studio\u003c/ul\u003e\n\u003cp\u003e\nEach SAS application is presented with explanation of its strengths, weaknesses, and best uses. Even users of automated forecasting systems will benefit from this knowledge of what is done and why. Moreover, the accompanying examples can serve as templates that you easily adjust to fit your specific forecasting needs. \n\u003cp\u003e\nThis book is part of the SAS Press program.
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