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A comparative study of linear and nonlinear models for aggregate retail sales forecasting

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  • Chu, Ching-Wu
  • Zhang, Guoqiang Peter

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  • Chu, Ching-Wu & Zhang, Guoqiang Peter, 2003. "A comparative study of linear and nonlinear models for aggregate retail sales forecasting," International Journal of Production Economics, Elsevier, vol. 86(3), pages 217-231, December.
  • Handle: RePEc:eee:proeco:v:86:y:2003:i:3:p:217-231
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    References listed on IDEAS

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    1. Callen, Jeffrey L. & Kwan, Clarence C. Y. & Yip, Patrick C. Y. & Yuan, Yufei, 1996. "Neural network forecasting of quarterly accounting earnings," International Journal of Forecasting, Elsevier, vol. 12(4), pages 475-482, December.
    2. De Gooijer, Jan G. & Franses, Philip Hans, 1997. "Forecasting and seasonality," International Journal of Forecasting, Elsevier, vol. 13(3), pages 303-305, September.
    3. Ghysels, Eric & Granger, Clive W J & Siklos, Pierre L, 1996. "Is Seasonal Adjustment a Linear or Nonlinear Data-Filtering Process? Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 396-397, July.
    4. Ghysels, Eric & Granger, Clive W J & Siklos, Pierre L, 1996. "Is Seasonal Adjustment a Linear or Nonlinear Data-Filtering Process?," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 374-386, July.
    5. Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
    6. Hung, Ming S. & Denton, James W., 1993. "Training neural networks with the GRG2 nonlinear optimizer," European Journal of Operational Research, Elsevier, vol. 69(1), pages 83-91, August.
    7. Goodrich, Robert L., 2000. "The Forecast Pro methodology," International Journal of Forecasting, Elsevier, vol. 16(4), pages 533-535.
    8. Barksdale, Hiram C & Hilliard, Jimmy E, 1975. "A Cross-spectral Analysis of Retail Inventories and Sales," The Journal of Business, University of Chicago Press, vol. 48(3), pages 365-382, July.
    9. Gorr, Wilpen L., 1994. "Editorial: Research prospective on neural network forecasting," International Journal of Forecasting, Elsevier, vol. 10(1), pages 1-4, June.
    10. Prybutok, Victor R. & Yi, Junsub & Mitchell, David, 2000. "Comparison of neural network models with ARIMA and regression models for prediction of Houston's daily maximum ozone concentrations," European Journal of Operational Research, Elsevier, vol. 122(1), pages 31-40, April.
    11. Luxhoj, James T. & Riis, Jens O. & Stensballe, Brian, 1996. "A hybrid econometric--neural network modeling approach for sales forecasting," International Journal of Production Economics, Elsevier, vol. 43(2-3), pages 175-192, June.
    12. Franses, Philip Hans & Draisma, Gerrit, 1997. "Recognizing changing seasonal patterns using artificial neural networks," Journal of Econometrics, Elsevier, vol. 81(1), pages 273-280, November.
    13. Darbellay, Georges A. & Slama, Marek, 2000. "Forecasting the short-term demand for electricity: Do neural networks stand a better chance?," International Journal of Forecasting, Elsevier, vol. 16(1), pages 71-83.
    14. Kirby, Howard R. & Watson, Susan M. & Dougherty, Mark S., 1997. "Should we use neural networks or statistical models for short-term motorway traffic forecasting?," International Journal of Forecasting, Elsevier, vol. 13(1), pages 43-50, March.
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    Cited by:

    1. Au, Kin-Fan & Choi, Tsan-Ming & Yu, Yong, 2008. "Fashion retail forecasting by evolutionary neural networks," International Journal of Production Economics, Elsevier, vol. 114(2), pages 615-630, August.
    2. Pakravan, Mohammad Reza & Kalashami, Mohammad Kavoosi, 2011. "Future prospects of Iran, U.S and Turkey's Pistachio exports," International Journal of Agricultural Management and Development (IJAMAD), Iranian Association of Agricultural Economics, vol. 1(3), September.
    3. Gur Ali, Ozden & Pinar, Efe, 2016. "Multi-period-ahead forecasting with residual extrapolation and information sharing — Utilizing a multitude of retail series," International Journal of Forecasting, Elsevier, vol. 32(2), pages 502-517.
    4. Aye, Goodness C. & Balcilar, Mehmet & Gupta, Rangan & Majumdar, Anandamayee, 2015. "Forecasting aggregate retail sales: The case of South Africa," International Journal of Production Economics, Elsevier, vol. 160(C), pages 66-79.
    5. Wong, W.K. & Guo, Z.X., 2010. "A hybrid intelligent model for medium-term sales forecasting in fashion retail supply chains using extreme learning machine and harmony search algorithm," International Journal of Production Economics, Elsevier, vol. 128(2), pages 614-624, December.
    6. Nikolopoulos, K. & Goodwin, P. & Patelis, A. & Assimakopoulos, V., 2007. "Forecasting with cue information: A comparison of multiple regression with alternative forecasting approaches," European Journal of Operational Research, Elsevier, vol. 180(1), pages 354-368, July.
    7. Sa-ngasoongsong, Akkarapol & Bukkapatnam, Satish T.S. & Kim, Jaebeom & Iyer, Parameshwaran S. & Suresh, R.P., 2012. "Multi-step sales forecasting in automotive industry based on structural relationship identification," International Journal of Production Economics, Elsevier, vol. 140(2), pages 875-887.
    8. Pakravan, Mohammad Reza & Kavoosi Kalashami, Mohammad & Alipour, Hamid Reza, 2011. "Forecasting Iran’s Rice Imports Trend During 2009-2013," International Journal of Agricultural Management and Development (IJAMAD), Iranian Association of Agricultural Economics, vol. 1(1), March.
    9. repec:bbz:fcpbbr:v:8:y:2011:i:2:p:01-21 is not listed on IDEAS
    10. Zhang, Ningning & Lin, Aijing & Shang, Pengjian, 2017. "Multidimensional k-nearest neighbor model based on EEMD for financial time series forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 477(C), pages 161-173.

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