Seasonal Time Series and Transfer Function Modelling for Natural Rubber Forecasting in India

International Journal of Computer Trends and Technology (IJCTT)          
© - May Issue 2013 by IJCTT Journal
Volume-4 Issue-5                           
Year of Publication : 2013
Authors :P. Arumugam, V. Anithakumari


P. Arumugam, V. Anithakumari"Seasonal Time Series and Transfer Function Modelling for Natural Rubber Forecasting in India"International Journal of Computer Trends and Technology (IJCTT),V4(5):1366-1370 May Issue 2013 .ISSN Published by Seventh Sense Research Group.

Abstract: - Time series analysis is a powerful tool to determine dynamic models aiming at defining and controlling most appropriate variables of a system. Transfer function model is one of the popular techniques in the time series modelling for forecasting. When there is an output series which is inclined by an input series, the objective of the transfer function modelling is to identify the role of input series in determining the variable of interest. In this paper, the Transfer Function model is fitted to the Natural Rubber production in India. The Transfer function Model has been used to identify a model and estimate parameters for forecasting of rubber production.


[1] Bovas A.” Seasonal Time series and Transfer Function Modeling,” Journal of Business & Economic Statisticsvol vol .3,,No, 3(4),pp 356- 361,Oct1985.
[2] Monica chiogna,carlo Galtan, Guide Masarotto,”Automatic Identification of seasonal Transfer model by means of Iteration stepwise and Genetic Algorithm.Department of science statistic .Journal of Time series Analysis vol 29,No 1,pp. 37-50 ,2007.
[3] Box, G.E.P, and G.M. Jenkins and G.C.Reinsel, Time series analysis Forecasting and control, 4 th edition, John Wiley and sons, Inc., New Jersey, 1998.
[4] Maria emila camargo, Walter priesnite filtio,Angela dos santoes Dullius,”Transfer function and intervention model for the study of Brazilian inflationary process,African journal of business Managemeny Vol.4(5),PP-578-582,May2010,ISSN 1993-8233@2010
[5] Bambang Widjanarko Otok and Suhartono, “Development of Rainfall Forecasting Model in Indonesia by using ASTAR, Transfer Function and ARIMA Methods,” European Journal of Scientific Research, Vol.38 No. 3(2009),pp.386-395
[6] Walialak Atthir awong and Porntip Chatchaipun,”Time series Analysis for Natural Field Latex Prices Prediction,” King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, Thailand 2010.
[7] A.A, Khin, Zainalabidin M.and Mad.Nasir.S,” Comparative Forecasting Models Accuracy of Short- term Natural Rubber Prices,” Trends in Agricultural Economics4 (1):1-17, 2011, ISSN 1994- 7933/DOI: 10.3923/tae.2011.1.17.
[8] Chinye S. Mesike,” Short term forecasting of Nigerian natural rubber export, “Wudpecker journals of Agricultural Research, Vol. 1(10), pp. 396-400,(2012).
[9] Mad nasir shamsudin and Fatimah mohd arshad,”Composite Model for Short Term Forecasting for Natural Rubber Prices” Pertanika 13(2),283-288(1990), 43400 UPM Serdang, Selangor Darul Ehsan, Malaysia.
[10] Lon Lmliu, “Forecasting residential consumption of natural gas using monthly and quarterly time series “, International journal of forecasting 7(1991)3-16, pp.3-16 North Holland.

Keywords — Time series, Transfer function, Autoregressive Integrated Moving Average Model, Cross correlation Function.