2017, Vol. 2, Issue 6, Part C
Estimation of non-linear models for fitting growth curves of cotton in IndiaAuthor(s):
Sundar Rajan M and Palanivel MAbstract:
The objective of this study were to compare the goodness of fit of six non-linear growth model Monomolecular, Logistic, Gompertz, Richards, Quadratic and Reciprocal growth in India Cotton Area, Production and Productivity data collected during 1950-2012. The models parameters (a, b and c), Coefficient of Determination (R2
), Residual Sum of Square (RSS) and Root Mean Square Error (RMSE) results. The “Run test” and “Shapiro-Wilk” test were also used to test the compliance of the error term to the underlying assumptions. Among the six models, under study predicted closely the observed values of top area, production and productivity in the selected nonlinear growth model has been selected for its accuracy of fit according to the highest R2
, Lower Residual Sum of Square and Mean Square Error.Pages: 190-196 | Views: 1097 | Downloads: 14Download Full Article: Click Here
How to cite this article:
Sundar Rajan M, Palanivel M. Estimation of non-linear models for fitting growth curves of cotton in India. Int J Stat Appl Math 2017;2(6):190-196.