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Research Article Open access CC BY 4.0

Statistical Modeling for Analysis of Growth and Trend Pattern of Wheat Production in Selected States of India

Manish Kumar, Gyan Prakash, Shiv Kumar Rana

Asian Journal of Research in Crop Science · pp. 66–75 · Published 17 Jan 2024

10.9734/ajrcs/2024/v9i1246

Abstract

In the present paper, the time series analysis of wheat production in some selected states of India has been carried out by fitting well-known statistical models, viz. linear, exponential and cubic models. The selection of wheat growing states has been made on the basis of criteria of higher production and consistent growth pattern. The secondary time series data on wheat production have been utilized for the analysis. The trend values have been computed on fitting the concerned models, and the validity of the models has been tested on using the chi-square test statistic. Moreover, the coefficient of determination ( ), root mean square error (RMSE), and relative mean absolute percentage error (RMAPE) have been computed to reveal the suitability of the concerned models for exploring the trend patterns of wheat production in the concerned states of India. The findings of the investigation reveal that the above mentioned models are appropriate for forecasting of future trend of wheat production in the concerned states.

Time series linear model exponential model cubic model chi-square test coefficient of determination

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