Boshnakov, G.N. (2016) Introduction to Time Series Analysis and Forecasting, 2nd Edition, Wiley Series in Probability and Statistics, by Douglas C. Montgomery, Cheryl L. Jennings and Murat Kulahci (eds). Published by John Wiley and Sons, Hoboken, NJ, USA, 2015. Total Number of Pages: 672 Hardcover: ISBN: 978-1-118-74511-3, ebook: ISBN: 978-1-118-74515-1, etext: ISBN: 978-1-118-74495-6. Journal of Time Series Analysis, 37, 864.
https://doi.org/10.1111/jtsa.12203

has been cited by the following article:

• TITLE: An Econometric Time Series GDP Model Analysis: Statistical Evidences and Investigations

  AUTHORS: Habib Ahmed Elsayir

  KEYWORDS: ARIMA Model, GDP, Box-Jenkins Models, Stationary Time Series

  JOURNAL NAME: Journal of Applied Mathematics and Physics, Vol.6 No.12, December 27, 2018

  ABSTRACT: This article aims to provide an analysis for a time series data of gross domestic product (GDP) of the Sudan. An econometric time series model with macroeconomic variables is conducted. Since a non-stationary time series must be made stationary, some statistical tests are followed so that the time series become stationary series. After applying these tests, the time series became stationary and integrated of order I. Box-Jenkins procedure is used to determine ARMA. OLS is used to estimate the models parameters. Performances chosen ARIMA model are verified on the basis of classical statistical tests and forecasting. The model features are interpreted on the basis of standard measures of forecasting performance.