Abstract
Numerous literatures on statistical methods for Time-Series (TS) data have been published. In this paper, a literature of the TS data analysis methods is reviewed. We organize the review based on the basic three-family category of TS models: The Exponential Smoothing Model (ESM) family, the Auto-Regressive Integrated Moving Average (ARIMA) model family, and the Unobserved Component Model (UCM) family. A roadmap is provided in a diagram format to these TS methods which are translatable into nowadays computing statements. Further, the execution of these methods in SAS commands (as one of the most popular nowadays statistical software packages) is also presented. This paper will be very beneficial for practitioners, forecasters, and researchers in diverse fields of study (such as business, management, finance, economics, etc.) to determine which TS data analysis method (along with the corresponding SAS command) are ready to use.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
