Optimum Fitting of Richards Growth Model in Random Environment
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Richards four-parameter nonlinear growth model is a very versatile model for describing many growth processes. Two limitations of the corresponding Richards nonlinear statistical model are discussed. Accordingly, in this article, the general approach of ‘Stochastic differential equations’ is considered. Ghosh and Prajneshu (J Indian Soc Agric Stat 71:127–138, 2017) developed the methodology for fitting Richards growth model in random environment, when one of the parameters, viz. m takes a particular value. Purpose of the present article is to extend this type of work by proposing the methodology, which is valid for all values of m. Relevant computer programs for its application are written and the same are included as an “Appendix”. Finally, as an illustration, pig growth data are considered and superiority of our proposed model is shown over the Richards nonlinear statistical model for given data.
KeywordsRichards nonlinear growth model Stochastic differential equation Out-of-sample forecasting
Mathematics Subject Classification65C30
The authors are grateful to Science and Engineering Research Board, New Delhi for providing financial assistance under Research Project No. SB/S4/MS/880/2014. Thanks are also due to the referees for their valuable comments.
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