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2024, Vol. 9, Special Issue 5

Forecasting models for area, production and productivity of wheat in North Gujarat


Author(s): DM Padalia, GK Chaudhary, PB Marviya, LK Kumawat, IB Savaliya and Tejas S

Abstract: The present study was carried out to estimate the trends of area, production and productivity of wheat in North Gujarat. Yearly time series data on area, production and productivity of wheat of North Gujarat for the period of 1991-92 to 2021-22 were collected from the published reports by Directorate of Agriculture, Gujarat state, Gandhinagar. Polynomial and Autoregressive Integrated Moving Average (ARIMA) models were applied to analyze the area, production and productivity of wheat in North Gujarat. First, second and third-degree polynomial models were fitted to the original data and moving averages, with the best model selected based on adjusted R², Root Mean Square Error (RMSE), Mean Absolute Error (MAE), normality by the Shapiro-Wilk (1965) test and randomness of residuals by the Run test. ARIMA models were evaluated for stationarity and different orders (p, d, q) were assessed using autocorrelation function (ACF), partial autocorrelation function (PACF) and the models were selected on the basis of significant autoregressive and moving average term, lower value of Akaike’s Information Criteria (AIC) and Schwartz-Bayesian Criteria (SBC) and normality of residuals by Shapiro-Wilk (1965) test and Box-Ljung (1978) test. The cubic polynomial model on a four year moving average was most suitable for wheat production trends, while ARIMA (0, 2, 1) and ARIMA (0, 2, 2) were optimal for wheat area and production patterns.

DOI: 10.22271/maths.2024.v9.i5Sc.1829

Pages: 149-157 | Views: 54 | Downloads: 2

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How to cite this article:
DM Padalia, GK Chaudhary, PB Marviya, LK Kumawat, IB Savaliya, Tejas S. Forecasting models for area, production and productivity of wheat in North Gujarat. Int J Stat Appl Math 2024;9(5S):149-157. DOI: 10.22271/maths.2024.v9.i5Sc.1829

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