International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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India | Statistics | Volume 3 Issue 7, July 2014 | Pages: 1002 - 1006


Forecasting of Areca Nut (Areca catechu) Yield Using Arima Model for Uttara Kannada District of Karnataka

Srinath Reddy A. B., Havaldar Y. N., Pavan Kumar S. T., Adam Kamei

Abstract: Arecanut (Areca catechu) also popular by name supari or betelnut. It is one of important commercial crop in Uttara Kannada district, contributing around 9 percent of area and 11 percent of production to the Karnataka state total. The present study is based on the secondary data of over 30 years collected from Directorate of Economics and Statistics. The prediction of arecanut production on a yearly time scales has been attempted by various research groups using different techniques models. Among the most effective approaches for analyzing time series data is the model introduced by Box and Jenkins, ARIMA (Autoregressive Integrated Moving Average). The selection of models was done based on their R2 value and root mean square error (RMSE) value after analyzing the data, and further these models were used for prediction of arecanut production. From the different (p. d. q) models, ARIMA (1, 1, 5) was selected based on RMSE (0.325) and normalised BIC (-1.319) values for forecasting the production of arecanut in Uttara Kannada district. The model parameters were estimated using SPSS software and hence it was taken as best fitted model and forecasting has been done

Keywords: Mean square error, Nonlinear, ARIMA, SPSS, AIC, BIC

How to Cite?: Srinath Reddy A. B., Havaldar Y. N., Pavan Kumar S. T., Adam Kamei, "Forecasting of Areca Nut (Areca catechu) Yield Using Arima Model for Uttara Kannada District of Karnataka", Volume 3 Issue 7, July 2014, International Journal of Science and Research (IJSR), Pages: 1002-1006, https://www.ijsr.net/getabstract.php?paperid=12071411, DOI: https://dx.doi.org/10.21275/12071411


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