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Asian Journal of Applied Sciences
  Year: 2011 | Volume: 4 | Issue: 1 | Page No.: 42-52
DOI: 10.3923/ajaps.2011.42.52
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Application of Parametric and Nonparametric Regression Models for Area, Production and Productivity Trends of Castor (Ricinus communis L.) Crop

A. Rajarathinam and R.S. Parmar

The present investigation was carried out to study area, production and productivity trends and growth rates of castor crop grown in Anand district of middle Gujarat in India for the period 1949-50 to 2007-08. In parametric models different linear, non-linear and time-series models were employed. The statistically most suited parametric models were selected on the basis of adjusted R2, significant regression co-efficients and co-efficient of determination (R2). Appropriate time-series models were fitted after judging the time-series data for stationarity. The statistically appropriate model was selected on the basis of various goodness of fit criteria viz., Akaike’s Information Criterion, Bayesian Information Criterion, Root Mean Square Error, Mean Absolute Error, assumptions of normality and independence of residuals. In nonparametric regression optimum bandwidth was computed by cross-validation method. Epanechnikov-kernel was used as the weight function. Nonparametric estimates of underlying growth function were computed at each and every time point. Residual analysis was carried out to test the randomness. Relative growth rates of area, production and productivity were estimated based on the best fitted trend function. The nonparametric regression model emerged as the best fitted trend functions for the area, production and productivity of castor crop. The per cent growth rate values obtained for the successive years during the period under study for area, production and productivity when averaged showed that the production had increased at a rate of 5.79% per annum which was due to combined effect of increase in area and productivity at a rate of 2.86 and 3.41% per annum, respectively.
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  •    A Simulated Annealing for the Single Machine Batch Scheduling with Deterioration and Precedence Constraints
  •    Toxicity and Nutritive Assessment of Castor (Ricinus cummunis) Oil and Processed Cake in Rat Diet
  •    Effect of Transformation on the Parameter Estimates of a Simple Linear Regression Model: A Case Study of Division of Variables by Constants
  •    Some Consequences of Adding a Constant to at Least One of the Variables in the Simple Linear Regression Model
How to cite this article:

A. Rajarathinam and R.S. Parmar, 2011. Application of Parametric and Nonparametric Regression Models for Area, Production and Productivity Trends of Castor (Ricinus communis L.) Crop. Asian Journal of Applied Sciences, 4: 42-52.

DOI: 10.3923/ajaps.2011.42.52






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