@article{MAKHILLJMMS20137128185,
    title = {Using Normalized BIC to Improve Box-Jenkins Model Building},
    journal = {Journal of Modern Mathematics and Statistics},
    volume = {7},
    number = {1},
    pages = {1-7},
    year = {2013},
    issn = {1994-5388},
    doi = {jmmstat.2013.1.7},
    url = {https://makhillpublications.co/view-article.php?issn=1994-5388&doi=jmmstat.2013.1.7},
    author = {E.P.},
    keywords = {ARIMA Model,normalized Bayesian Information Criterion (BIC),Box-Jenkins approach,Ljung-Box statistic,time series analysis},
    abstract = {The Box-Jenkins Model building approach is used to fit a statistical 
  time series model to the chemical viscosity reading data. The data were extracted 
  from Box-Jenkins in called series D. The Normalized BIC was explored to compare 
  the fitted ARIMA (1, 1, 1) Model with both the AR (1) and IMA (1, 1) Models 
  fitted originally to the same series by Box-Jenkins in 1976. Among this class 
  of significantly adequate set of ARIMA (p, d, q) Models of the same data set, 
  the ARIMA (1, 1, 1) Model was found as the most suitable model with least BIC 
  value of -2.366, MAPE of 2.424, RMSE of 0.301 and R<SUP>2</SUP> of 0.749. Estimation 
  by Ljung-Box test with Q (18) = 9.746, 16 d.f and p-value of 0.880 showed no 
  autocorrelation between residuals at different lag times. Finally, a forecast 
  for a lead time (l) of 12 was made.}
    }