Follow
International Journal of Current Microbiology and Applied Sciences (IJCMAS)
IJCMAS is now DOI (CrossRef) registered Research Journal. The DOIs are assigned to all published IJCMAS Articles.
Index Copernicus ICI Journals Master List 2022 - IJCMAS--ICV 2022: 95.28 For more details click here
National Academy of Agricultural Sciences (NAAS) : NAAS Score: *5.38 (2020) [Effective from January 1, 2020] For more details click here

Login as a Reviewer


See Guidelines to Authors
Current Issues
Download Publication Certificate

Original Research Articles                      Volume : 9, Issue:11, November, 2020

PRINT ISSN : 2319-7692
Online ISSN : 2319-7706
Issues : 12 per year
Publisher : Excellent Publishers
Email : editorijcmas@gmail.com /
submit@ijcmas.com
Editor-in-chief: Dr.M.Prakash
Index Copernicus ICV 2018: 95.39
NAAS RATING 2020: 5.38

Int.J.Curr.Microbiol.App.Sci.2020.9(11): 84-93
DOI: https://doi.org/10.20546/ijcmas.2020.911.009


Statistical Evaluation of Stepwise Regression Method and Autoregressive Integrated Moving Average Method for Forecasting of Groundnut (Arachis hypogaea L.) Productivity in Junagadh District of Gujarat
K.Sathees Kumar1*and Mayur Shitap2
1Department of Agricultural Statistics, Bidhan Chandra Krishi Viswavidyalaya, Mohanpur, Nadia741 252, West Bengal, India
2Department of Agricultural Statistics, Junagadh Agricultural University, Junagadh-362 001, Gujarat, India
*Corresponding author
Abstract:

In India, the productivity of various crops is unstable mainly due to climatic factors, price volatility and resource availability. The pre-harvest forecasting of the crop productivity is a major priority to know about the market demand of the crops. The present study focused the ability of pre-harvest forecasting performance of stepwise regression method and the ARIMA method. In stepwise regression method, two approaches were developed namely (1) using week-wise original weather variable and (2) weather indices using correlation coefficient as weight. Among the two approaches studied, the correlation coefficient as a weighted approach had more expedient to pre-harvest forecasting of groundnut. Eventually, after the good interrogation, stepwise regression method had better puissance than the ARIMA method for forecasting the groundnut productivity in the Junagadh district of Gujarat.


Keywords: ARIMA, Stepwise regression, Weather indices

Download this article as Download

How to cite this article:

Sathees Kumar, K. and Mayur Shitap. 2020. Statistical Evaluation of Stepwise Regression Method and Autoregressive Integrated Moving Average Method for Forecasting of Groundnut (Arachis hypogaea L.) Productivity in Junagadh District of Gujarat.Int.J.Curr.Microbiol.App.Sci. 9(11): 84-93. doi: https://doi.org/10.20546/ijcmas.2020.911.009
Copyright: This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike license.

Citations