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Time series analysis using SAS Enter...

Liu, Shuangzhe.

Time series analysis using SAS Enterprise guide

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Time series analysis using SAS Enterprise guideby Timina Liu, Shuangzhe Liu, Lei Shi.
作者:	Liu, Timina.
其他作者:	Liu, Shuangzhe.
出版者:	Singapore :Springer Singapore :2020.
面頁冊數:	viii, 131 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Time-series analysis.
電子資源:	https://doi.org/10.1007/978-981-15-0321-4
ISBN:	9789811503214$q(electronic bk.)

Time series analysis using SAS Enterprise guide
Liu, Timina.

Time series analysis using SAS Enterprise guide[electronic resource] /by Timina Liu, Shuangzhe Liu, Lei Shi. - Singapore :Springer Singapore :2020. - viii, 131 p. :ill., digital ;24 cm. - SpringerBriefs in statistics,2191-544X. - SpringerBriefs in statistics..

1 Introduction -- 1.1 Overview -- 1.2 SAS Enterprise Guide -- 2 Basic Statistics and Regression Models -- 2.1 Calculating New Variables -- 2.2 Normality Test -- 2.3 Simple Linear Regression -- 2.4 Multiple Linear Regression -- 3 Time Series -- 3.1 Smoothing Methods -- 3.2 ARIMA Model -- 3.3 Regression Model with AR Errors -- 4 Panel Models -- 4.1 Fixed effect -- 4.2 Random Effect -- References.

This is the first book to present time series analysis using the SAS Enterprise Guide software. It includes some starting background and theory to various time series analysis techniques, and demonstrates the data analysis process and the final results via step-by-step extensive illustrations of the SAS Enterprise Guide software. This book is a practical guide to time series analyses in SAS Enterprise Guide, and is valuable resource that benefits a wide variety of sectors.

ISBN: 9789811503214$q(electronic bk.)

Standard No.: 10.1007/978-981-15-0321-4doiSubjects--Topical Terms:

181890
Time-series analysis.

LC Class. No.: QA280 / .L588 2020

Dewey Class. No.: 519.55

Time series analysis using SAS Enterprise guide
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505 0 $a 1 Introduction -- 1.1 Overview -- 1.2 SAS Enterprise Guide -- 2 Basic Statistics and Regression Models -- 2.1 Calculating New Variables -- 2.2 Normality Test -- 2.3 Simple Linear Regression -- 2.4 Multiple Linear Regression -- 3 Time Series -- 3.1 Smoothing Methods -- 3.2 ARIMA Model -- 3.3 Regression Model with AR Errors -- 4 Panel Models -- 4.1 Fixed effect -- 4.2 Random Effect -- References.
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