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Martin, J., de Adana, D.D.R. and Asuero, A.G. (2017) Fitting Models to Data: Residual Analysis, a Primer, Uncertainty Quantification and Model Calibration. Jan Peter Hessling, IntechOpen.
https://www.intechopen.com/books/uncertainty-quantification-and-model-calibration/fitting-models-to-data-residual-analysis-a-primer

has been cited by the following article:

• TITLE: Residual Analysis for Auto-Correlated Econometric Model

  AUTHORS: Habib Ahmed Elsayir

  KEYWORDS: ARIMA Model, Autocorrelation, GDP, Residual Analysis

  JOURNAL NAME: Open Journal of Statistics, Vol.9 No.1, January 25, 2019

  ABSTRACT: The aim of this article is to provide residual analysis for a time series data of Gross Domestic Product (GDP) of the Sudan. An econometric time series model with macroeconomic variables is conducted to examine the goodness of fit using residual. Many statistical tests are used in time series models in order to make it a stationary series. After applying these tests, the time series became stationary and integrated; thus, Box-Jenkins procedure is used for the determination of ARIMA, AR (0,1,0) in this study. This identified technique is useful for analyzing this study.